Prediction Apparatus and Prediction Method

• US 20110238428A1
• Filed: 03/29/2011
• Published: 09/29/2011
• Est. Priority Date: 03/29/2010
• Status: Abandoned Application

• Current Assignee: Bank of Tokyo-Mitsubishi UFJ Limited (Mitsubishi UFJ Financial Group Incorporated)
• Original Assignee: Bank of Tokyo-Mitsubishi UFJ Limited (Mitsubishi UFJ Financial Group Incorporated)
• Inventors: KAWAMOTO, Hideo
• Application Number:
  US13/074,315
• Publication Number:
  US 20110238428A1
• Time in Patent Office: Days
• US Class Current: 705/1.1
• CPC Class Codes: G06F 2209/5019 Workload prediction
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03

Abstract

A prediction apparatus predicts an upper limit of the number of job executions per unit period in a system which executes a job responding to a request from outside. The prediction apparatus firstly acquires a sample data regarding the job. The sample data to be acquired is a sample data from which the number of job executions for each unit period in the past can be identified. Then, based on a distribution of the number of job executions identified from the sample data, the upper limit of the number of job executions per unit period in the future is predicted. Thereafter, the predicted upper limit is outputted.

Claims

1. A prediction apparatus that predicts an upper limit of a number of job executions per unit period in a system executing a job responding to a request from outside, comprising:

an acquisition device that acquires a sample data regarding the job, from which a number of job executions for each unit period in a past can be identified; and

a prediction device that predicts the upper limit of the number of job executions per unit period in a future, based on a distribution of the number of job executions for each unit period identified from the sample data, and then outputs the predicted upper limit.

2. The prediction apparatus according to claim 1, wherein

the prediction device:

calculates a value of an endpoint of a confidence interval at a predetermined confidence level of the number of job executions per unit period, based on the number of job executions for each unit period identified from the sample data, on an assumption that a probability distribution of the number of job executions per unit period follows a normal distribution; and

predicts the upper limit of the number of job executions per unit period based on the value of the endpoint of the confidence interval.

3. The prediction apparatus according to claim 2, wherein

the prediction device predicts a value of the upper endpoint of the confidence interval to be the upper limit of the number of job executions per unit period.

4. The prediction apparatus according to claim 1, wherein

the prediction device calculates the probability distribution of the number of job executions per unit period, based on the number of job executions for each unit period identified from the sample data, and predicts the upper limit of the number of job executions per unit period based on the calculated probability distribution.

5. The prediction apparatus according to claim 4, wherein

the prediction device predicts a minimum value of the number of job executions per unit period in a range where a cumulative probability is greater than a specific probability to be the upper limit of the number of job executions per unit period, the cumulative probability being a cumulative probability of the number of job executions per unit period and changing in accordance with the number of job executions per unit period, which functions as a variable, and

the cumulative probability is calculated by accumulating an occurrence probability for each value of the number of job executions per unit period identified from the probability distribution, in ascending order of the value of the number of job executions per unit period, up to a value of the number of job executions per unit period corresponding to the variable.

6. The prediction apparatus according to claim 4, wherein

the prediction device calculates the probability distribution with an action of correction to show unimodality, and predicts the upper limit of the number of job executions per unit period based on the calculated probability distribution.

7. The prediction apparatus according to claim 1, wherein

the system is a system which executes as the job a transaction responding to a request from outside, and

the prediction device predicts, as the number of job executions per unit period, an upper limit of a number of transactions per unit period in the system.

8. A recording medium that is computer-readable and stores a program which causes a computer to execute processing of predicting an upper limit of a number of job executions per unit period in a system executing a job responding to a request from outside,

the processing comprising:

a procedure that acquires a sample data regarding the job, from which a number of job executions for each unit period in a past can be identified; and

a procedure that predicts the upper limit of the number of job executions per unit period in a future, based on a distribution of the number of job executions for each unit period identified from the sample data, and outputting the predicted upper limit.

9. A prediction method that predicts an upper limit of a number of job executions per unit period in a system executing a job responding to a request from outside, comprising:

an acquisition procedure that acquires a sample data regarding the job, from which a number of job executions for each unit period in a past can be identified; and

a prediction procedure that predicts the upper limit of the number of job executions per unit period in a future, based on a distribution of the number of job executions for each unit period identified from the sample data, and then outputting the predicted upper limit.

10. The prediction method according to claim 9, wherein

the prediction procedure is a procedure that

calculates a value of an endpoint of a confidence interval at a predetermined confidence level of the number of job executions per unit period, based on the number of job executions for each unit period identified from the sample data, on an assumption that a probability distribution of the number of job executions per unit period follows a normal distribution, and

predicts the upper limit of the number of job executions per unit period based on the value of the endpoint of the confidence interval.

11. The prediction method according to claim 10, wherein

the prediction procedure is a procedure that predicts a value of the upper endpoint of the confidence interval to be the upper limit of the number of job executions per unit period.

12. The prediction method according to claim 9, wherein

the prediction procedure is a procedure that

calculates a probability distribution of the number of job executions per unit period, based on the number of job executions for each unit period identified from the sample data, and

predicts the upper limit of the number of job executions per unit period, based on the calculated probability distribution.

13. The prediction method according to claim 12, wherein

the prediction procedure is a procedure that predicts a minimum value of the number of job executions per unit period in a range where a cumulative probability is greater than a specific probability to be the upper limit of the number of job executions per unit period, the cumulative probability being a cumulative probability of the number of job executions per unit period and changing in accordance with the number of job executions per unit period, which functions as a variable, and

the cumulative probability is calculated by accumulating an occurrence probability for each value of the number of job executions per unit period identified from the probability distribution, in ascending order of the value of the number of job executions per unit period, up to a value of the number of job executions per unit period corresponding to the variable.

14. The prediction method according to claim 12, wherein

the prediction procedure is a procedure that calculates the probability distribution with an action of correction to show unimodality, and predicts the upper limit of the number of job executions per unit period based on the calculated probability distribution.

15. The prediction method according to claim 9, wherein

the system is a system which executes a transaction responding to a request from outside, and

the prediction procedure is a procedure that predicts an upper limit of a number of transactions per unit period in the system, as the number of job executions per unit period.

16. A prediction apparatus that predicts an upper limit of a number of transactions per unit period for a specific type of transaction involving market prices, comprising:

an acquisition device that acquires a sample data regarding the specific type of transaction, from which a number of transactions for each unit period in a past and a market price fluctuation amount for each unit period in the past can be identified;

a basic fluctuation amount calculation device that calculates a basic fluctuation amount, based on the number of transactions and the market price fluctuation amount for each unit period identified from the sample data, the basic fluctuation amount being a fluctuation amount of the number of transactions per unit period relative to the market price fluctuation amount;

a basic transactions calculation device that calculates, for each unit period, a basic number of transactions, based on the basic fluctuation amount, and the number of transactions and the market price fluctuation amount for each unit period, the basic number of transactions being a number of transactions per unit period on an assumption that market price fluctuations do not exist; and

a prediction device that predicts the upper limit of the number of transactions per unit period for the specific type of transaction, based on a distribution of the basic number of transactions identified from the basic number of transactions for each unit period, a distribution of the market price fluctuation amount identified from the market price fluctuation amount for each unit period and the basic fluctuation amount, and then outputs the predicted upper limit,

wherein

the basic transactions calculation device

estimates, for each unit period, a fluctuation amount of the number of transactions caused by market price fluctuations in the period, based on the basic fluctuation amount and the market price fluctuation amount for each unit period,

calculates the basic number of transactions by subtracting an absolute value of the estimated fluctuation amount from an actual number of transactions in the period identified from the sample data, when the estimated fluctuation amount is positive, and

calculates the basic number of transactions by adding the absolute value of the estimated fluctuation amount to the actual number of transactions, when the estimated fluctuation amount is negative.

17. The prediction apparatus according to claim 16,

wherein the basic fluctuation amount calculation device

calculates, as the basic fluctuation amount, a first basic fluctuation amount and a second basic fluctuation amount,

calculates, as the first basic fluctuation amount, a basic fluctuation amount during a market price appreciation, based on the number of transactions and the market price fluctuation amount for each unit period in a first period in which the market price fluctuation amount is positive, among the numbers of transactions and the market price fluctuation amounts for each unit period identified from the sample data, and

calculates, as the second basic fluctuation amount, a basic fluctuation amount during a market price depreciation, based on the number of transactions and the market price fluctuation amount for each unit period in a second period in which the market price fluctuation amount is negative,

wherein the basic transactions calculation device calculates, as the basic number of transactions for each unit period,

a basic number of transactions for each unit period in the first period using the first basic fluctuation amount, and

a basic number of transactions for each unit period in the second period using the second basic fluctuation amount.

18. The prediction apparatus according to claim 16,

the prediction device comprising:

a first confidence interval endpoint calculation device that calculates a value of an endpoint of a confidence interval at a predetermined confidence level of the basic number of transactions, based on the basic number of transactions for unit period; and

a second confidence interval endpoint calculation device that calculates a value of an endpoint of a confidence interval at a predetermined confidence level of the market price fluctuation amount, based on the market price fluctuation amount for unit period,

wherein the prediction device predicts the upper limit of the number of transactions per unit period for the specific type of transaction, based on a calculated value by the first confidence interval endpoint calculation device, a calculated value by the second confidence interval endpoint calculation device and the basic fluctuation amount.

19. The prediction apparatus according to claim 17,

the prediction device comprising:

a first confidence interval endpoint calculation device that calculates a value of an endpoint of a confidence interval at a predetermined confidence level of the basic number of transactions, based on the basic number of transactions for each unit period; and

a second confidence interval endpoint calculation device that calculates values of endpoints of a confidence interval at a predetermined confidence level of the market price fluctuation amount, based on the market price fluctuation amount for each unit period,

wherein the prediction device predicts an upper limit of the number of transactions per unit period during a market price appreciation and an upper limit of the number of transactions per unit period during a market price depreciation, as the upper limit of the number of transactions for the specific type of transaction, based on a calculated value by the first confidence interval endpoint calculation device, calculated values by the second confidence interval endpoint calculation device and the first and second basic fluctuation amounts, and outputs a larger upper limit of both the predicted upper limits.

20. The prediction apparatus according to claim 18, wherein

the prediction device

predicts an upper limit of the fluctuation amount of the number of transactions per unit period associated with market price fluctuations, based on the calculated value by the second confidence interval endpoint calculation device and the basic fluctuation amount, while predicting an upper limit of the number of transactions per unit period when market price fluctuations do not exist, based on the calculated value by the first confidence interval endpoint calculation device, and

predicts a value obtained by adding the predicted upper limit of the fluctuation amount of the number of transactions per unit period to the predicted upper limit of the number of transactions per unit period when market price fluctuations do not exist, to be the upper limit of the number of transactions per unit period for the specific type of transaction.

21. The prediction apparatus according to claim 19, wherein

the prediction device:

predicts a first upper limit and a second upper limit based on the calculated values by the second confidence interval endpoint calculation device and the first and second basic fluctuation amounts, while predicting a third upper limit based on the calculated value by the first confidence interval endpoint calculation device,

the first upper limit being an upper limit of the fluctuation amount of the number of transactions per unit period associated with market price fluctuations during the market price appreciation,

the second upper limit being an upper limit of the fluctuation amount of the number of transactions per unit period associated with market price fluctuations during the market price depreciation, and

the third upper limit being an upper limit of the number of transactions per unit period when market price fluctuations do not exist;

predicts a value obtained by adding the predicted first upper limit to the predicted third upper limit to be the upper limit of the number of transactions per unit period during the market price appreciation; and

predicts a value obtained by adding the predicted second upper limit to the predicted third upper limit to be the upper limit of the number of transactions per unit period during the market price depreciation.

22. The prediction apparatus according to claim 16,

the prediction device comprising:

a transactions distribution calculation device that calculates a probability distribution of the basic number of transactions, based on the number of transactions for each unit period; and

a fluctuation amount distribution calculation device that calculates a probability distribution of the market price fluctuation amount, based on the market price fluctuation amount for each unit period,

wherein the prediction device

calculates, based on an occurrence probability P(R) for each value R of the basic number of transactions identified from the probability distribution of the basic number of transactions, an occurrence probability P(G) for each value G of the market price fluctuation amount identified from the probability distribution of the market price fluctuation amount, and a value K of the basic fluctuation amount, for each combination (R, G) of the value R and the value G, an occurrence probability P(R)·

P(G) of the number of transactions Es=(R+K·

G) per unit period corresponding to the combination, and

predicts a minimum value of the number of transactions Es per unit period in a range where a cumulative probability is greater than a specific probability to be the upper limit of the number of transactions per unit period for the specific type of transaction, the cumulative probability being a cumulative probability of the number of transactions Es per unit period and changing in accordance with the number of transactions Es per unit period, which functions as a variable,

wherein the cumulative probability is calculated by accumulating the occurrence probability P(R)·

P(G) for each combination (R, G), in ascending order of a value of the number of transactions Es per unit period, up to a value of the number of transactions Es per unit period corresponding to the variable.

23. The prediction apparatus according to claim 17,

the prediction device comprising:

a transactions distribution calculation device that calculates a probability distribution of the basic number of transactions, based on the basic number of transactions for each unit period; and

a fluctuation amount distribution calculation device that calculates a probability distribution of the market price fluctuation amount, based on the market price fluctuation amount for each unit period,

wherein, the prediction device

calculates, based on an occurrence probability P(R) for each value R of the basic number of transactions identified from the probability distribution of the basic number of transactions, an occurrence probability P(G) for each value G of the market price fluctuation amount identified from the probability distribution of the market price fluctuation amount, and a value KH of the first basic fluctuation amount and a value KL of the second basic fluctuation amount, for each combination (R, G) of the value R and the value G, a number of transactions Es=(R+K·

G) per unit period, using the value KH as a value K when the value G is positive and using the value KL as the value K when the value G is negative, while calculating an occurrence probability P(R)·

P(G) of the number of transactions Es per unit period, and

predicts a minimum value of the number of transactions Es per unit period in a range where a cumulative probability is greater than a specific probability to be the upper limit of the number of transactions per unit period for the specific type of transaction, the cumulative probability being a cumulative probability of the number of transactions Es per unit period and changing in accordance with the number of transactions Es per unit period, which functions as a variable,

wherein the cumulative probability is calculated by accumulating the occurrence probability P(R)·

P(G) for each combination (R, G), in ascending order of a value of the number of transactions Es per unit period, up to a value of the number of transactions Es per unit period corresponding to the variable.

24. The prediction apparatus according to claim 22, wherein at least one of the transactions distribution calculation device and the fluctuation amount distribution calculation device calculates the corresponding probability distribution, with an action of correction to show unimodality.

25. The prediction apparatus according to claim 22, wherein

the transactions distribution calculation device

corrects a frequency distribution of the basic number of transactions based on the basic number of transactions for each unit period, so that the frequency is monotonically nonincreasing in an interval in which the basic number of transactions is larger than that having a highest frequency, and so that the frequency is monotonically nondecreasing in an interval in which the basic number of transactions is smaller than that having the highest frequency, and

transforms the frequency distribution after correction into a probability distribution to calculate the probability distribution of the basic number of transactions showing unimodality.

26. The prediction apparatus according to claim 22, wherein

the fluctuation amount distribution calculation device

corrects a frequency distribution of the market price fluctuation amount based on the market price fluctuation amount for each unit period, so that the frequency is monotonically nonincreasing in an interval in which the market price fluctuation amount is larger than that having a highest frequency, and so that the frequency is monotonically nondecreasing in an interval in which the market price fluctuation amount is smaller than that having the highest frequency, and

transforms the frequency distribution after correction into a probability distribution to calculate the probability distribution of the market price fluctuation amount showing unimodality.

27. The prediction apparatus according to claim 16, wherein the basic fluctuation amount calculation device performs a linear regression analysis of the number of transactions and the market price fluctuation amount for each unit period to calculate the basic fluctuation amount.

28. The prediction apparatus according to claim 17, wherein

the basic fluctuation amount calculation device performs

a linear regression analysis of the number of transactions and the market price fluctuation amount for each unit period in the first period to calculate the first basic fluctuation amount, and

a linear regression analysis of the number of transactions and the market price fluctuation amount for each unit period in the second period to calculate the second basic fluctuation amount.

29. The prediction apparatus according to claim 16, wherein the basic transactions calculation device estimates, for each unit period, a value obtained by multiplying the market price fluctuation amount in the period identified from the sample data by the basic fluctuation amount, to be the fluctuation amount of the number of transactions caused by market price fluctuations in the period.

30. The prediction apparatus according to claim 17, wherein

the basic transactions calculation device

estimates, for the unit period in which the market price fluctuation amount is positive, a value obtained by multiplying the market price fluctuation amount in the period identified from the sample data by the first basic fluctuation amount, to be the fluctuation amount of the number of transactions caused by market price fluctuations in the period, and

estimates, for the unit period in which the market price fluctuation amount is negative, a value obtained by multiplying the market price fluctuation amount in the period identified from the sample data by the second basic fluctuation amount, to be the fluctuation amount of the number of transactions caused by market price fluctuations in the period.

31. The prediction apparatus according to claim 16, wherein the acquisition device acquires, as the sample data, a sample data from which the number of transactions for each unit period and the market price fluctuation amount for each unit period during at least one of a market price appreciation period and a market price depreciation period can be identified.

32. The prediction apparatus according to claim 16, wherein

the acquisition device acquires, as the sample data, a sample data from which the number of transactions per user for each unit period in the past and the market price fluctuation amount for each unit period in the past can be identified,

the basic fluctuation amount calculation device calculates, as the basic fluctuation amount, a fluctuation amount of the number of transactions per user relative to the market price fluctuation amount, based on the number of transactions per user and the market price fluctuation amount for each unit period identified from the sample data,

the basic transactions calculation device calculates, for each unit period, as the basic number of transactions, the number of transactions per user per period on an assumption that market price fluctuations do not exist, based on the number of transactions per user for each unit period, the basic fluctuation amount and the market price fluctuation amount for each unit period, and

the prediction device predicts, as the upper limit of the number of transactions per unit period for the specific type of transaction, an upper limit of the number of transactions per user.

33. The prediction apparatus according to claim 32, comprising a necessary capacity calculation device that

calculates a recording capacity Z necessary for an information processing system executing processing relating to the specific type of transaction, by a formula Z=Q1+D·

Q2·

Q3, based on

a fixed necessary volume Q1 which is a recording capacity fixedly necessary for the information processing system,

a predicted value Q2 of the upper limit of the number of transactions per user,

an assumed number of users Q3, and

an increase ratio D of the necessary recording capacity per transaction, and

outputs the calculated recording capacity Z.

34. A recording medium that is computer-readable and records a program which causes a computer to execute processing that predicts an upper limit of a number of transactions per unit period for a specific type of transaction involving market prices,

the processing comprising:

a procedure that acquires a sample data regarding the specific type of transaction, from which a number of transactions for each unit period in a past and a market price fluctuation amount for each unit period in the past can be identified;

a procedure that calculates a basic fluctuation amount, based on the number of transactions and the market price fluctuation amount for each unit period identified from the sample data, the basic fluctuation amount being a fluctuation amount of the number of transactions per unit period relative to the market price fluctuation amount;

a procedure that calculates, for each unit period, a basic number of transactions, based on the basic fluctuation amount, and the number of transactions and the market price fluctuation amount for each unit period, the basic number of transactions being a number of transactions per unit period on an assumption that market price fluctuations do not exist; and

a procedure that predicts the upper limit of the number of transactions per unit period for the specific type of transaction, based on a distribution of the basic number of transactions identified from the basic number of transactions for each unit period, a distribution of the market price fluctuation amount identified from the market price fluctuation amount for each unit period and the basic fluctuation amount, and then outputting the predicted upper limit,

wherein the procedure that calculates the basic number of transactions is a procedure that

estimates, for each unit period, the fluctuation amount of the number of transactions caused by market price fluctuations in the period, based on the basic fluctuation amount and the market price fluctuation amount for each unit period,

calculates the basic number of transactions by subtracting an absolute value of the estimated fluctuation amount from an actual number of transactions in the period identified from the sample data, when the estimated fluctuation amount is positive, and

calculates the basic number of transactions by adding the absolute value of the estimated fluctuation amount to the actual number of transactions, when the estimated fluctuation amount is negative.

35. A prediction method that predicts an upper limit of a number of transactions per unit period for a specific type of transaction involving market prices, comprising:

an acquisition procedure that acquires a sample data regarding the specific type of transaction, from which a number of transactions for each unit period in a past and a market price fluctuation amount for each unit period in the past can be identified;

a basic fluctuation amount calculation procedure that calculates a basic fluctuation amount, based on the number of transactions and the market price fluctuation amount for each unit period identified from the sample data, the basic fluctuation amount being a fluctuation amount of the number of transactions per unit period relative to the market price fluctuation amount;

a basic transactions calculation procedure that calculates, for each unit period, a basic number of transactions, based on the basic fluctuation amount, and the number of transactions and the market price fluctuation amount for each unit period, the basic number of transactions being a number of transactions per unit period on an assumption that market price fluctuations do not exist; and

a prediction procedure that predicts the upper limit of the number of transactions per unit period for the specific type of transaction, based on a distribution of the basic number of transactions identified from the basic number of transactions for each unit period, a distribution of the market price fluctuation amount identified from the market price fluctuation amount for each unit period, and the basic fluctuation amount, and outputting the predicted upper limit,

wherein the basic transactions calculation procedure is a procedure that

estimates, for each unit period, a fluctuation amount of the number of transactions caused by market price fluctuations in the period, based on the basic fluctuation amount and the market price fluctuation amount for each unit period,

calculates the basic number of transactions by subtracting an absolute value of the estimated fluctuation amount from an actual number of transactions in the period identified from the sample data, when the estimated fluctuation amount is positive, and

calculates the basic number of transactions by adding the absolute value of the estimated fluctuation amount to the actual number of transactions, when the estimated fluctuation amount is negative.

36. The prediction method according to claim 35, wherein

the basic fluctuation amount calculation procedure,

calculates a first basic fluctuation amount and a second basic fluctuation amount, as the basic fluctuation amount,

calculates the basic fluctuation amount during a market price appreciation, as the first basic fluctuation amount, based on the number of transactions and the market price fluctuation amount for each unit period in a first period in which the market price fluctuation amount is positive, among the numbers of transactions and the market price fluctuation amounts for each unit period identified from the sample data, and

calculates the basic fluctuation amount during a market price depreciation, as the second basic fluctuation amount, based on the number of transactions and the market price fluctuation amount for each unit period in a second period in which the market price fluctuation amount is negative,

wherein the basic transactions calculation procedure is a procedure that calculates, as the basic number of transactions for each unit period, the basic number of transactions for each unit period in the first period using the first basic fluctuation amount, and calculating the basic number of transactions for each unit period in the second period using the second basic fluctuation amount.

37. The prediction method according to claim 35,

the prediction procedure comprising:

a first confidence interval endpoint calculation procedure that calculates a value of an endpoint of a confidence interval at a predetermined confidence level of the basic number of transactions, based on the basic number of transactions for each unit period; and

a second confidence interval endpoint calculation procedure that calculates a value of an endpoint of a confidence interval at a predetermined confidence level of the market price fluctuation amount, based on the market price fluctuation amount for each unit period,

wherein the prediction procedure is a procedure that predicts the upper limit of the number of transactions per unit period for the specific type of transaction, based on a calculated value by the first confidence interval endpoint calculation procedure, a calculated value by the second confidence interval endpoint calculation procedure and the basic fluctuation amount.

38. The prediction method according to claim 36,

the prediction procedure comprising:

a first confidence interval endpoint calculation procedure that calculates a value of an endpoint of a confidence interval at a predetermined confidence level of the basic number of transactions, based on the basic number of transactions for each unit period; and

a second confidence interval endpoint calculation procedure that calculates values of endpoints of a confidence interval at a predetermined confidence level of the market price fluctuation amount, based on the market price fluctuation amount for each unit period,

wherein the prediction procedure predicts an upper limit of the number of transactions per unit period during the market price appreciation and an upper limit of the number of transactions per unit period during the market price depreciation, as the upper limit of the number of transactions for the specific type of transaction, based on a calculated value by the first confidence interval endpoint calculation procedure, calculated values by the second confidence interval endpoint calculation procedure and the first and second basic fluctuation amounts, and outputs a larger upper limit of the predicted upper limits.

39. The prediction method according to claim 35,

the prediction procedure comprising:

a transactions distribution calculation procedure that calculates a probability distribution of the basic number of transactions, based on the number of transactions for each unit period; and

a fluctuation amount distribution calculation procedure that calculates a probability distribution of the market price fluctuation amount, based on the market price fluctuation amount for each unit period,

wherein the prediction procedure is a procedure that

calculates, based on an occurrence probability P(R) for each value R of the basic number of transactions identified from the probability distribution of the basic number of transactions, an occurrence probability P(G) for each value G of the basic fluctuation amount identified from the probability distribution of the market price fluctuation amount, and a value K of the market price fluctuation amount, for each combination (R, G) of the value R and the value G, an occurrence probability P(R)·

P(G) of the number of transactions Es=(R+K·

G) per unit period corresponding to the combination, and

predicts a minimum value of the number of transactions Es per unit period in a range where a cumulative probability is greater than a specific probability to be the upper limit of the number of transactions per unit period for the specific type of transaction, the cumulative probability being a cumulative probability of the number of transactions Es per unit period and changing in accordance with the number of transactions Es per unit period, which functions as a variable,

wherein the cumulative probability is calculated by accumulating the occurrence probability P(R)·

P(G) for each combination (R, G), in ascending order of a value of the number of transactions Es per unit period, up to a value of the number of transactions Es per unit period corresponding to the variable.

40. The prediction method according to claim 36,

the prediction procedure comprising:

a transactions distribution calculation procedure that calculates a probability distribution of the basic number of transactions, based on the number of transactions for each unit period; and

a fluctuation amount distribution calculation procedure that calculates a probability distribution of the market price fluctuation amount, based on the market price fluctuation amount for each unit period,

wherein the prediction procedure is a procedure that

calculates, based on an occurrence probability P(R) for each value R of the basic number of transactions identified from the probability distribution of the basic number of transactions, an occurrence probability P(G) for each value G of the market price fluctuation amount identified from the probability distribution of the market price fluctuation amount, and a value KH of the first basic fluctuation amount and a value KL of the second basic market price fluctuation amount, for each combination (R, G) of the value R and the value G, the number of transactions Es=(R+K·

G) per unit period, using the value KH as a value K when the value G is positive and the value KL as the value K when the value G is negative, while calculating an occurrence probability P(R)·

P(G) of the number of transactions Es per unit period, and

predicts a minimum value of the number of transactions Es per unit period in a range where a cumulative probability is greater than a specific probability to be the upper limit of the number of transactions per unit period for the specific type of transaction, the cumulative probability being a cumulative probability of the number of transactions Es per unit period and changing in accordance with the number of transactions Es per unit period, which functions as a variable,

wherein the cumulative probability is calculated by accumulating the occurrence probability P(R)·

P(G) for each combination (R, G), in ascending order of a value of the number of transactions Es per unit period, up to a value of the number of transactions Es per unit period corresponding to the variable.

41. The prediction method according to claim 39, wherein

at least one of the transactions distribution calculation procedure and the fluctuation amount distribution calculation procedure is a procedure that calculates the corresponding probability distribution with an action of correction to show unimodality.

42. A prediction apparatus that predicts an upper limit of a momentary number of jobs, the momentary number of jobs being a number of job executions in a short time period for a system executing a job responding to a request from outside, comprising:

an acquisition device that acquires a sample data regarding the job, from which

a number of job executions for each unit period in a past can be identified, and

a concentration ratio for each unit period in the past can be further identified, the concentration ratio being a ratio of a largest momentary number of jobs in the unit period to the number of job executions in the unit period;

a jobs distribution calculation device that calculates a probability distribution of the number of jobs per unit period, based on the number of job executions for each unit period identified from the sample data;

a concentration ratio distribution calculation device that calculates a probability distribution of the concentration ratio, based on the concentration ratio for each unit period identified from the sample data; and

a prediction device that predicts the upper limit of the momentary number of jobs, based on an occurrence probability P(A) for each value A of the number of job executions per unit period identified from the probability distribution of the number of job executions and an occurrence probability P(B) for each value B of the concentration ratio identified from the probability distribution of the concentration ratio, and outputs the predicted upper limit.

43. The prediction apparatus according to claim 42,

wherein the prediction device

calculates, based on the occurrence probability P(A) for each value A of the number of job executions per unit period and the occurrence probability P(B) for each value B of the concentration ratio, for each combination (A, B) of the value A and the value B, an occurrence probability P(A)·

P(B) of the momentary number of jobs Qs=A·

B corresponding to the combination, and

predicts a minimum value of the momentary number of jobs Qs in a range where a cumulative probability is greater than a specific probability to be the upper limit of the momentary number of jobs, the cumulative probability being a cumulative probability of the momentary number of jobs Qs and changing in accordance with the momentary number of jobs Qs, which functions as a variable,

wherein the cumulative probability is calculated by accumulating the occurrence probability P(A)·

P(B) for each combination (A, B) in ascending order of a value of the momentary number of jobs Qs, up to a value of the momentary number of jobs Qs corresponding to the variable.

44. The prediction apparatus according to claim 42, wherein

at least one of the jobs distribution calculation device and the concentration ratio distribution calculation device calculates the corresponding probability distribution with an action of correction to show unimodality.

45. The prediction apparatus according to claim 42, wherein

the system is a system which executes a transaction responding to a request from outside as the job, and

the prediction device predicts, as the upper limit of the momentary number of jobs, the upper limit of the momentary number of transactions, that is a number of transactions in a short time period in the system.

46. The prediction apparatus according to claim 42, wherein

the system is an information processing system in which an operation unit executes the job, and

the prediction apparatus includes an operation units calculation device that calculates a number of operation units necessary for the information processing system, based on a number of jobs which can be simultaneously processed per operation unit and the upper limit of the momentary number of jobs predicted by the prediction device, and outputs the calculated number of operation units.

47. A recording medium that is computer-readable and records a program which causes a computer to execute processing that predicts an upper limit of a momentary number of jobs, the momentary number of jobs being a number of job executions in a short time period in a system executing a job responding to a request from outside,

the processing comprising:

a procedure that acquires a sample data regarding the job, from which

a number of job executions for each unit period in a past can be identified, and

a concentration ratio for each unit period in the past can be further identified, the concentration ratio being a ratio of a largest momentary number of jobs in the unit period to the number of job executions in the unit period;

a procedure that calculates a probability distribution of the number of jobs per unit period, based on the number of job executions for each unit period identified from the sample data;

a procedure that calculates a probability distribution of the concentration ratio, based on the concentration ratio for each unit period identified from the sample data; and

a procedure that predicts the upper limit of the momentary number of jobs, based on an occurrence probability P(A) for each value A of the number of job executions per unit period identified from the probability distribution of the number of job executions and an occurrence probability P(B) for each value B of the concentration ratio identified from the probability distribution of the concentration ratio, and outputting the predicted upper limit.

48. A prediction method that predicts an upper limit of a momentary number of jobs, the momentary number of jobs being a number of job executions in a short time period in a system executing a job responding to a request from outside, comprising:

an acquisition procedure that acquires a sample data regarding the job, from which

a number of job executions for each unit period in a past can be identified, and

a concentration ratio for each unit period in the past can be further identified, the concentration ratio being a ratio of a largest momentary number of jobs in the unit period to the number of job executions in the unit period;

a jobs distribution calculation procedure that calculates a probability distribution of the number of job executions per unit period, based on the number of job executions for each unit period identified from the sample data;

a concentration ratio distribution calculation procedure that calculates a probability distribution of the concentration ratio, based on the concentration ratio for each unit period identified from the sample data; and

a prediction procedure that predicts the upper limit of the momentary number of jobs, based on an occurrence probability P(A) for each value A of the number of job executions per unit period identified from the probability distribution of the number of job executions and an occurrence probability P(B) for each value B of the concentration ratio identified from the probability distribution of the concentration ratio, and outputs the predicted upper limit.

49. The prediction method according to claim 48, wherein

the prediction procedure is a procedure that:

calculates, based on the occurrence probability P(A) for each value A of the number of job executions per unit period and the occurrence probability P(B) for each value B of the concentration ratio, for each combination (A, B) of the value A and the value B, an occurrence probability P(A)·

P(B) of the momentary number of jobs Qs=A·

B corresponding to the combination, and

predicts a minimum value of the momentary number of jobs Qs in a range where a cumulative probability is greater than a specific probability to be the upper limit of the momentary number of jobs, the cumulative probability being a cumulative probability of the momentary number of jobs Qs and changing in accordance with the momentary number of jobs Qs, which functions as a variable,

wherein the cumulative probability is calculated by accumulating the occurrence probability P(A)·

P(B) for each combination (A, B) in ascending order of a value of the momentary number of jobs Qs, up to a value of the momentary number of jobs Qs corresponding to the variable.

50. The prediction method according to claim 48, wherein at least one of the jobs distribution calculation procedure and the concentration ratio distribution calculation procedure is a procedure that calculates the corresponding probability distribution with an action of correction to show unimodality.

51. A prediction apparatus that predicts an upper limit of a momentary number of transactions for a specific type of transaction involving market prices, comprising:

an acquisition device that acquires a sample data regarding the specific type of transaction, from which

a number of transactions and a market price fluctuation amount for each unit period in a past can be identified, and

a concentration ratio for each unit period in the past can be further identified, the concentration ratio being a ratio of a largest momentary number of jobs in the unit period to the number of transactions in the unit period;

a basic fluctuation amount calculation device that calculates a basic fluctuation amount, based on the number of transactions and the market price fluctuation amount for each unit period identified from the sample data, the basic fluctuation amount being a fluctuation amount of the number of transactions per unit period relative to the market price fluctuation amount;

a basic transactions calculation device that calculates a basic number of transactions for each unit period, based on the basic fluctuation amount, and the number of transactions and the market price fluctuation amount for each unit period, the basic number of transactions being a number of transactions per unit period on an assumption that market price fluctuations do not exist;

a transactions distribution calculation device that calculates a probability distribution of the basic number of transactions, based on the basic number of transactions for each unit period;

a fluctuation amount distribution calculation device that calculates a probability distribution of the market price fluctuation amount, based on the market price fluctuation amount for each unit period;

a concentration ratio distribution calculation device that calculates a probability distribution of the concentration ratio, based on the concentration ratio for each unit period identified from the sample data;

a prediction device that predicts the upper limit of the momentary number of transactions, based on an occurrence probability P(R) for each value R of the basic number of transactions identified from the probability distribution of the basic number of transactions, an occurrence probability P(G) for each value G of the market price fluctuation amount identified from the probability distribution of the market price fluctuation amount, an occurrence probability P(B) for each value B of the concentration ratio identified from the probability distribution of the concentration ratio, and a value K of the basic fluctuation amount, and outputs the predicted upper limit,

wherein the basic transactions calculation device

estimates, based on the basic fluctuation amount and the market price fluctuation amount for each unit period, for each unit period, a fluctuation amount of the number of transactions caused by market price fluctuations in the period,

calculates the basic number of transactions by subtracting an absolute value of the estimated fluctuation amount from an actual number of transactions in the period identified from the sample data, when the estimated fluctuation amount is positive, and

calculates the basic number of transactions by adding the absolute value of the estimated fluctuation amount to the actual number of transactions, when the estimated fluctuation amount is negative.

52. The prediction apparatus according to claim 51,

wherein the prediction device

calculates, based on the occurrence probability P(R) for each value R of the basic number of transactions, the occurrence probability P(G) for each value G of the market price fluctuation amount, the occurrence probability P(B) for each value B of the concentration ratio, and the value K of the basic fluctuation amount, for each combination (R, G, B) of the value R, the value G and the value B, an occurrence probability P(R)·

P(G)·

P(B) of the momentary number of transactions Qs=(R+K·

G)·

B corresponding to the combination, and

predicts a minimum value of the momentary number of transactions Qs in a range where a cumulative probability is greater than a specific probability to be the upper limit of the momentary number of transactions for the specific type of transaction, the cumulative probability being a cumulative probability of the momentary number of transactions Qs and changing in accordance with the momentary number of transactions Qs, which functions as a variable,

wherein the cumulative probability is calculated by accumulating the occurrence probability P(R)·

P(G)·

P(B) for each combination (R, G, B) in ascending order of a value of the momentary number of transactions Qs, up to a value of the momentary number of transactions Qs corresponding to the variable.

53. The prediction apparatus according to claim 51, wherein at least one of the transactions distribution calculation device, the fluctuation amount distribution calculation device and the concentration ratio distribution calculation device calculates the corresponding probability distribution with an action of correction to show unimodality.

54. The prediction apparatus according to claim 51, wherein

the transactions distribution calculation device

corrects a frequency distribution of the basic number of transactions based on the basic number of transactions for each unit period, so that the frequency is monotonically nonincreasing in an interval in which the basic number of transactions is larger than that having a highest frequency, and so that the frequency is monotonically nondecreasing in an interval in which the basic number of transactions is smaller than that having the highest frequency, and

transforms the frequency distribution after correction into a probability distribution to calculate the probability distribution of the basic number of transactions showing unimodality.

55. The prediction apparatus according to claim 51, wherein

the fluctuation amount distribution calculation device

corrects a frequency distribution of the market price fluctuation amount based on the market price fluctuation amount for each unit period, so that the frequency is monotonically nonincreasing in an interval in which the market price fluctuation amount is larger than that having a highest frequency, and so that the frequency is monotonically nondecreasing in an interval in which the market price fluctuation amount is smaller than that having the highest frequency, and

transforms the frequency distribution after correction into a probability distribution to calculate the probability distribution of the market price fluctuation amount showing unimodality.

56. The prediction apparatus according to claim 51, wherein

the concentration ratio distribution calculation device

corrects a frequency distribution of the concentration ratio based on the concentration ratio for each unit period, so that the frequency is monotonically nonincreasing in an interval in which the concentration ratio is larger than that having a highest frequency, and so that the frequency is monotonically nondecreasing in an interval in which the concentration ratio is smaller than that having the highest frequency, and

transforms the frequency distribution after correction into a probability distribution to calculate the probability distribution of the concentration ratio showing unimodality.

57. The prediction apparatus according to claim 51, wherein

the basic fluctuation amount calculation device performs a linear regression analysis of the number of transactions and the market price fluctuation amount for each unit period to calculate the basic fluctuation amount.

58. The prediction apparatus according to claim 51, comprising an operation units calculation device that calculates a number of operation units necessary for an information processing system executing processing relating to the specific type of transaction based on a number of transactions which can be simultaneously processed per operation unit and the upper limit of the momentary number of transactions predicted by the prediction device, and outputs the calculated number of operation units.

59. The prediction apparatus according to claim 58, wherein

the acquisition device acquires a sample data from which the number of transactions per user can be identified as the number of transactions,

the prediction device is configured to predict, as the upper limit of the momentary number of transactions, the upper limit of the momentary number of transactions per user, and

the operation units calculation device calculates the number of operation units, based on a previously assumed number of users, the number of transactions which can be simultaneously processed per operation unit, and the upper limit predicted by the prediction device.

60. A recording medium that is computer-readable and records a program which causes a computer to execute processing that predicts an upper limit of a momentary number of transactions for a specific type of transaction involving market prices,

the processing comprising:

a procedure that acquires a sample data regarding the specific type of transaction, from which

a number of transactions and a market price fluctuation amount for each unit period in a past can be identified, and

a concentration ratio for each unit period in the past can be further identified, the concentration ratio being a ratio of a largest momentary number of transactions in the period to the number of transactions in the period;

a procedure that calculates a basic fluctuation amount, based on the number of transactions and the market price fluctuation amount for each unit period identified from the sample data, the basic fluctuation amount being a fluctuation amount of the number of transactions per unit period relative to the market price fluctuation amount;

a procedure that calculates, for each unit period, a basic number of transactions, based on the basic fluctuation amount, and the number of transactions and the market price fluctuation amount for each unit period, the basic number of transactions being a number of transactions per unit period on an assumption that market price fluctuations do not exist;

a procedure that calculates a probability distribution of the basic number of transactions based on the basic number of transactions for each unit period;

a procedure that calculates a probability distribution of the market price fluctuation amount based on the market price fluctuation amount for each unit period;

a procedure that calculates a probability distribution of the concentration ratio, based on the concentration ratio for each unit period identified from the sample data; and

a procedure that predicts an upper limit of the momentary number of transactions and outputting the predicted upper limit, based on

an occurrence probability P(R) for each value R of the basic number of transactions identified from the probability distribution of the basic number of transactions,

an occurrence probability P(G) for each value G of the market price fluctuation amount identified from the probability distribution of the market price fluctuation amount,

an occurrence probability P(B) for each value B of the concentration ratio identified from the probability distribution of the concentration ratio, and

a value K of the basic fluctuation amount,

wherein, the procedure that calculates a basic number of transactions

estimates, for each unit period, a fluctuation amount of the number of transactions caused by market price fluctuations in the period, based on the basic fluctuation amount and the market price fluctuation amount for each unit period,

calculates the basic number of transactions by subtracting an absolute value of the estimated fluctuation amount from an actual number of transactions in the period identified from the sample data, when the estimated fluctuation amount is positive; and

calculates the basic number of transactions by adding the absolute value of the estimated fluctuation amount to the actual number of transactions, when the estimated fluctuation amount is negative.

61. A prediction method that predicts an upper limit of a momentary number of transactions for a specific type of transaction involving market prices, comprising:

an acquisition procedure that acquires a sample data regarding the specific type of transaction, from which

a number of transactions and a market price fluctuation amount for each unit period in a past can be identified, and

a concentration ratio for each unit period in the past can be further identified, the concentration ratio being a ratio of a largest momentary number of transactions in the period to the number of transactions in the period;

a basic fluctuation amount calculation procedure that calculates a basic fluctuation amount, based on the number of transactions and the market price fluctuation amount for each unit period identified from the sample data, the basic fluctuation amount being a fluctuation amount of the number of transactions per unit period relative to the market price fluctuation amount;

a basic transactions calculation procedure that calculates a basic number of transactions for each unit period, based on the basic fluctuation amount, and the number of transactions and the market price fluctuation amount for each unit period, the basic number of transactions being a number of transactions per unit period on an assumption that market price fluctuations do not exist;

a transactions distribution calculation procedure that calculates a probability distribution of the basic number of transactions, based on the number of transactions for each unit period;

a fluctuation amount distribution calculation procedure that calculates a probability distribution of the market price fluctuation amount, based on the market price fluctuation amount for each unit period;

a concentration ratio distribution calculation procedure that calculates a probability distribution of the concentration ratio, based on the concentration ratio for each unit period identified from the sample data; and

a prediction procedure that predicts the upper limit of the momentary number of transactions and outputs the predicted upper limit, based on

an occurrence probability P(R) for each value R of the basic number of transactions identified from the probability distribution of the basic number of transactions,

an occurrence probability P(G) for each value G of the market price fluctuation amount identified from the probability distribution of the market price fluctuation amount,

an occurrence probability P(B) for each value B of the concentration ratio identified from the probability distribution of the concentration ratio, and

a value K of the basic fluctuation amount,

wherein the basic transactions calculation procedure

estimates, for each unit period, a fluctuation amount of the number of transactions caused by market price fluctuations in the period, based on the basic fluctuation amount and the market price fluctuation amount for each unit period,

calculates the basic number of transactions by subtracting an absolute value of the estimated fluctuation amount from an actual number of transactions in the period identified from the sample data, when the estimated fluctuation amount is positive, and

calculates the basic number of transactions by adding the absolute value of the estimated fluctuation amount to the actual number of transactions, when the estimated fluctuation amount is negative.

62. The prediction method according to claim 61, wherein

the prediction procedure is a procedure that

calculates, based on the occurrence probability P(R) for each value R of the basic number of transactions, the occurrence probability P(G) for each value G of the market price fluctuation amount, the occurrence probability P(B) for each value B of the concentration ratio, and the value K of the basic fluctuation amount, for each combination (R, G, B) of the value R, the value G and the value B, an occurrence probability P(R)·

P(G)·

P(B) of the momentary number of transactions Qs=(R+K·

G)·

B corresponding to the combination, and

predicts a minimum value of the momentary number of transactions Qs in a range where a cumulative probability is greater than a specific probability to be the upper limit of the momentary number of transactions for the specific type of transaction, the cumulative probability being a cumulative probability of the momentary number of transactions Qs and changing in accordance with the momentary number of transactions Qs, which functions as a variable,

wherein the cumulative probability is calculated by accumulating the occurrence probability P(R)·

P(G)·

P(B) for each combination (R, G, B) in ascending order of a value of the momentary number of transactions Qs, up to a value of the momentary number of transactions Qs corresponding to the variable.

63. The prediction method according to claim 61, wherein

at least one of the transactions distribution calculation procedure, the fluctuation amount distribution calculation procedure and the concentration ratio distribution calculation procedure is a procedure that calculates the corresponding probability distribution with an action of correction to show unimodality.