Method of and system for analyzing, modeling and valuing elements of a business enterprise
First Claim
1. A computer-implemented network model method, comprising:
- receiving first input data into an initial network model to develop an initial model configuration;
receiving an input data set from said initial model configuration and a second input data as inputs into a second model stage to develop an improvement to said initial model configuration as an output, said second input data comprising one of said first input data, data not included in said first input data, and a combination thereof; and
receiving said second model stage output as an input into a third model stage to develop a final network model by evolving a network model using a plurality of genetic algorithms where said final network model supports a regression analysis.
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Abstract
An automated system (100) and method for analyzing, modeling and valuing elements of a business enterprise on a specified valuation date. The performance of the elements are analyzed using search algorithms and induction algorithms to determine the value drivers associated with each element. The induction algorithms are also used to create composite variables that relate element performance to enterprise revenue, expenses and changes in capital. Predictive models are then used to determine the correlation between the value drivers and the enterprise revenue, expenses and changes in capital. The correlation percentages for each value driver are then multiplied by capitalized value of future revenue, expenses and changes in capital, the resulting numbers for each value driver associated with each element are then added together to calculate a value for each element.
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Citations
85 Claims
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1. A computer-implemented network model method, comprising:
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receiving first input data into an initial network model to develop an initial model configuration; receiving an input data set from said initial model configuration and a second input data as inputs into a second model stage to develop an improvement to said initial model configuration as an output, said second input data comprising one of said first input data, data not included in said first input data, and a combination thereof; and receiving said second model stage output as an input into a third model stage to develop a final network model by evolving a network model using a plurality of genetic algorithms where said final network model supports a regression analysis. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 63, 64, 65, 66)
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13. A machine-readable medium tangibly embodying a program of machine-readable instructions executable by a digital processing apparatus to perform a network model method, comprising:
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receiving first input data into an initial network model to develop an initial model configuration; receiving an input data set from said initial model configuration and a second input data as inputs into a second model stage to develop an improvement to said initial model configuration as an output, said second input data comprising one of said first input data, data not included in said first input data, and a combination thereof; and receiving said second model stage output as an input into a third model stage to develop a final network model by evolving a network model using a plurality of genetic algorithms where said final network model supports a regression analysis. - View Dependent Claims (14, 15, 16, 17, 18)
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35. A machine-readable medium tangibly embodying a program of machine-readable instructions executable by a digital processing apparatus to perform a neural network model method, comprising:
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receiving first input data into an initial neural network model to develop an initial model configuration; receiving an input data set from said initial model configuration and a second input data as inputs into a second model stage to develop an improvement to said initial model configuration as an output, said second input data comprising one of said first input data, data not included in said first input data, and a combination thereof; and receiving said second model stage output as an input into a third model stage to develop a final neural network model by evolving a network model using a plurality of genetic algorithms where said final neural network model supports a regression analysis. - View Dependent Claims (36, 37, 38, 39, 40)
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57. A machine-readable medium tangibly embodying a program of machine-readable instructions executable by a digital processing apparatus to perform a neural network model method, comprising:
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receiving first input data into an initial neural network model to develop an initial model configuration; receiving an input data set from said initial model configuration and a second input data as inputs into a second, induction model stage to develop an improvement to said initial model configuration as an output, said second input data comprising one of said first input data, data not included in said first input data and a combination thereof; and receiving said second model stage output as an input into a third model stage to develop a final neural network model by evolving a network model using a plurality of genetic algorithms where said final neural network model supports a regression analysis. - View Dependent Claims (58, 59, 60, 61, 62)
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67. A network model system, comprising:
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networked computers each with a processor having circuitry to execute instructions;
a storage device available to each processor with sequences of instructions stored therein, which when executed cause the processors to;receive first input data into an initial network model to develop an initial model configuration; receive an input data set from said initial model configuration and a second input data as inputs into a second model stage to develop an improvement to said initial model configuration as an output, said second input data comprising one of said first input data, data not included in said first input data, and a combination thereof; and receive said second model stage output as an input into a third model stage to develop a final network model by evolving a network model using a plurality of genetic algorithms where said final network model supports a regression analysis. - View Dependent Claims (68, 69, 70, 71, 72)
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73. A neural network model system, comprising:
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a computer with a processor having circuitry to execute instructions;
a storage device available to said processor with sequences of instructions stored therein, which when executed cause the processor to;receive first input data into an initial neural network model to develop an initial model configuration; receive an input data set from said initial model configuration and a second input data as inputs into a second model stage to develop an improvement to said initial model configuration as an output, said second input data comprising one of said first input data, data not included in said first input data, and a combination thereof; and receive said second model stage output as an input into a third model stage to develop a final neural network model by evolving a neural network model using a plurality of genetic algorithms where said final neural network model supports a regression analysis. - View Dependent Claims (74, 75, 76, 77, 78)
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79. An advanced network model system, comprising:
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networked computers each with a processor having circuitry to execute instructions;
a storage device available to each processor with sequences of instructions stored therein, which when executed cause the processors to;receive first input data into an initial neural network model to develop an initial model configuration; receive an input data set from said initial model configuration and a second input data as inputs into a second, induction model stage to develop an improvement to said initial model configuration as an output, said second input data comprising one of said first input data, data not included in said first input data, and a combination thereof; and receive said second model stage output as an input into a third model stage to develop a final neural network model by evolving a neural network model using a plurality of genetic algorithms where said final neural network model supports a regression analysis. - View Dependent Claims (80, 81, 82, 83, 84)
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85-197. -197. (canceled)
Specification