System and method for filling gaps of missing data using source specified data
First Claim
1. A method for filling a gap of missing data using source specified data, comprising:
- analyzing a first set of data representative of utility consumption for a plurality of days to determine clusters of days of the week having similar utility consumption;
generating an individual profile of utility consumption for each cluster;
copying data from at least one individual profile into the gap to form a second set of data without any gaps; and
identifying and removing abnormal utility consumption data from the first series of data, wherein the identifying and removing step includes performing an outlier analysis on the data.
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Accused Products
Abstract
A method and apparatus are provided for filling a gap of missing data using source specified data. The method includes analyzing a first set of data representative of utility consumption for a plurality of days to determine clusters of days of the week having similar utility consumption. The method further includes generating an individual profile of utility consumption for each cluster, and copying data from at least one individual profile into the gap to form a second set of data without any gaps. A system for filling a gap of missing data using source specified data includes a microprocessor programmed to copy data from at least one individual profile into the gap, and to adjust the copied data up or down to account for local trend information adjacent to the gap.
145 Citations
62 Claims
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1. A method for filling a gap of missing data using source specified data, comprising:
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analyzing a first set of data representative of utility consumption for a plurality of days to determine clusters of days of the week having similar utility consumption;
generating an individual profile of utility consumption for each cluster;
copying data from at least one individual profile into the gap to form a second set of data without any gaps; and
identifying and removing abnormal utility consumption data from the first series of data, wherein the identifying and removing step includes performing an outlier analysis on the data. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A method for filling a gap of missing data using source specified data, comprising:
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analyzing a first set of data representative of utility consumption for a plurality of days to determine clusters of days of the week having similar utility consumption;
generating an individual profile of utility consumption for each cluster; and
copying data from at least one individual profile into the gap to form a second set of data without any gaps, wherein the analyzing step includes performing a clustering algorithm. - View Dependent Claims (11)
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12. A method for filling a gap of missing data using source specified data, comprising:
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analyzing a first set of data representative of utility consumption for a plurality of days to determine clusters of days of the week having similar utility consumption;
generating an individual profile of utility consumption for each cluster; and
copying data from at least one individual profile into the gap to form a second set of data without any gaps, wherein the copying step includes adjusting the individual profile using statistics computed from data adjacent to the gap. - View Dependent Claims (13, 14, 15, 16, 17)
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18. A method for filling a gap of missing data using source specified data, comprising:
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analyzing a first set of data representative of utility consumption for a plurality of days to determine clusters of days of the week having similar utility consumption;
generating an individual profile of utility consumption for each cluster; and
copying data from at least one individual profile into the gap to form a second set of data without any gaps, wherein the first set of data is a time series of sufficient duration that each individual profile includes about 15 days worth of data prior to the gap and about 15 days worth of data following the gap. - View Dependent Claims (19)
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20. A method for filling a gap of missing data using source specified data, comprising:
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analyzing a first set of data representative of utility consumption for a plurality of days to determine clusters of days of the week having similar utility consumption;
generating an individual profile of utility consumption for each cluster;
copying data from at least one individual profile into the gap to form a second set of data without any gaps; and
displaying the second set of data on a display using indicia to distinguish the copied data. - View Dependent Claims (21)
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22. A method for filling a gap of missing data using source specified data, comprising:
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analyzing a first set of data representative of utility consumption for a plurality of days to determine clusters of days of the week having similar utility consumption;
generating an individual profile of utility consumption for each cluster;
copying data from at least one individual profile into the gap to form a second set of data without any gaps; and
performing summary calculations on the second set of data including the copied data. - View Dependent Claims (23, 24)
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25. An apparatus for filling a gap of missing data using source specified data, comprising:
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means for analyzing a first set of data representative of utility consumption for a plurality of days to determine clusters of days of the week having similar utility consumption;
means for generating an individual profile of utility consumption for each cluster; and
means for copying data from at least one individual profile into the gap to form a second set of data without any gaps, wherein the means for analyzing comprises a microprocessor programmed to perform a clustering algorithm. - View Dependent Claims (26)
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27. An apparatus for filling a gap of missing data using source specified data, comprising:
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means for analyzing a first set of data representative of utility consumption for a plurality of days to determine clusters of days of the week having similar utility consumption;
means for generating an individual profile of utility consumption for each cluster; and
means for copying data from at least one individual profile into the gap to form a second set of data without any gaps, wherein the means for copying includes means for adjusting the individual profile using statistics computed from data adjacent to the gap. - View Dependent Claims (28, 29, 30, 31, 32)
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33. An apparatus for filling a gap of missing data using source specified data, comprising:
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means for analyzing a first set of data representative of utility consumption for a plurality of days to determine clusters of days of the week having similar utility consumption;
means for generating an individual profile of utility consumption for each cluster; and
means for copying data from at least one individual profile into the gap to form a second set of data without any gaps, wherein the first set of data is a time series of sufficient duration that each individual profile includes about 15 days worth of data prior to the gap and about 15 days worth of data following the gap.
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34. A system for filling a gap of missing data using source specified data, the system comprising:
a programmed microprocessor configured to analyze a first set of data representative of utility consumption for a plurality of days to determine clusters of days of the week having similar utility consumption and to generate an individual profile of utility consumption data for each cluster, the microprocessor further configured to, copy data from at least one individual profile into the gap; and
adjust the copied data up or down to account for local trend information adjacent to the gap. - View Dependent Claims (35, 36, 37, 38, 39)
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40. A method for filling a gap of missing data using source specified data, comprising:
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analyzing a first set of data representative of utility consumption for a plurality of days to determine clusters of days of the week having similar utility consumption;
generating an individual profile of utility consumption for each cluster; and
copying data from at least one individual profile into the gap to form a second set of data without any gaps, wherein copying data includes adjusting the individual profile using at least one statistical Z-score computed for data adjacent to the gap. - View Dependent Claims (41, 42, 43, 44)
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45. A method for filling a gap of missing data using source specified data, comprising:
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analyzing a first set of data representative of utility consumption for a plurality of days to determine clusters of days of the week having similar utility consumption, wherein the first set of data is a time series of sufficient duration that each individual profile includes about 15 days worth of data prior to the gap and about 15 days worth of data following the gap;
generating an individual profile of utility consumption for each cluster; and
copying data from at least one individual profile into the gap to form a second set of data without any gaps. - View Dependent Claims (46)
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47. A method for filling a gap of missing data using source specified data, comprising:
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analyzing a first set of data representative of utility consumption for a plurality of days to determine clusters of days of the week having similar utility consumption;
generating an individual profile of utility consumption for each cluster;
copying data from at least one individual profile into the gap to form a second set of data without any gaps; and
displaying the second set of data on a display using indicia to distinguish the copied data. - View Dependent Claims (48)
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49. A method for filling a gap of missing data using source specified data, comprising:
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analyzing a first set of data representative of utility consumption for a plurality of days to determine clusters of days of the week having similar utility consumption;
generating an individual profile of utility consumption for each cluster;
copying data from at least one individual profile into the gap to form a second set of data without any gaps; and
performing summary calculations on the second set of data including the copied data. - View Dependent Claims (50, 51)
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52. An apparatus for filling a gap of missing data using source specified data, comprising:
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means for analyzing a first set of data representative of utility consumption for a plurality of days to determine clusters of days of the week having similar utility consumption;
means for generating an individual profile of utility consumption for each cluster; and
means for copying data from at least one individual profile into the gap to form a second set of data without any gaps, wherein the means for copying includes means for adjusting the individual profile using statistics computed from data adjacent to the gap, and wherein the means for adjusting the individual profile includes a microprocessor programmed to compute at least one statistical Z-score for data adjacent to the gap. - View Dependent Claims (53, 54, 55, 56)
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57. An apparatus for filling a gap of missing data using source specified data, comprising:
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means for analyzing a first set of data representative of utility consumption for a plurality of days to determine clusters of days of the week having similar utility consumption, wherein the first set of data is a time series of sufficient duration that each individual profile includes about 15 days worth of data prior to the gap and about 15 days worth of data following the gap;
means for generating an individual profile of utility consumption for each cluster; and
means for copying data from at least one individual profile into the gap to form a second set of data without any gaps.
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58. A system for filling a gap of missing data using source specified data, the system including a programmed microprocessor configured to analyze a first set of data representative of utility consumption for a plurality of days to determine clusters of days of the week having similar utility consumption and to generate an individual profile of utility consumption data for each cluster, the microprocessor further configured to:
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copy data from at least one individual profile into the gap; and
adjust the copied data up or down to account for local trend information adjacent to the gap, wherein the microprocessor is programmed to obtain the local trend information from time series data immediately prior to and/or following the gap.
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59. A system for filling a gap of missing data using source specified data, the system including a programmed microprocessor configured to analyze a first set of data representative of utility consumption for a plurality of days to determine clusters of days of the week having similar utility consumption and to generate an individual profile of utility consumption data for each cluster, the microprocessor further configured to:
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copy data from at least one individual profile into the gap; and
adjust the copied data up or down to account for local trend information adjacent to the gap, wherein the microprocessor is programmed to obtain the local trend information by determining at least one statistical Z-score for data adjacent to the gap. - View Dependent Claims (60, 61)
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62. A system for filling a gap of missing data using source specified data, the system including a programmed microprocessor configured to analyze a first set of data representative of utility consumption for a plurality of days to determine clusters of days of the week having similar utility consumption and to generate an individual profile of utility consumption for each cluster, the microprocessor further configured to:
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copy data from at least one individual profile into the gap; and
adjust the copied data up or down to account for local trend information adjacent to the gap, wherein the local trend information is based on approximately one day'"'"'s worth of data preceding the gap and approximately one day'"'"'s worth of data following the gap.
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Specification