Application of Genetic Programming to System Modeling from Input-Output Data

Sermsak UATRONGJIT; Nobuo FUJII

Application of Genetic Programming to System Modeling from Input-Output Data

Sermsak UATRONGJIT, Nobuo FUJII

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A new approach for generating a system model from its input-output data is presented. The model is approximated as a linear combination of simple basis functions. The number of basis functions is kept as small as possible to prevent over-fitting and to make the model efficiently computable. Based on these conditions, genetic programming is employed for the generation and selection of the appropriate basis. Since the obtained model can be expressed in simple mathematical expressions, it is suitable for using the model as a macro or behavior model in system level simulation. Experimental results are shown.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E81-A No.5 pp.924-930

Publication Date: 1998/05/25

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Category: Modeling and Simulation

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Sermsak UATRONGJIT, Nobuo FUJII, "Application of Genetic Programming to System Modeling from Input-Output Data" in IEICE TRANSACTIONS on Fundamentals, vol. E81-A, no. 5, pp. 924-930, May 1998, doi: .
Abstract: A new approach for generating a system model from its input-output data is presented. The model is approximated as a linear combination of simple basis functions. The number of basis functions is kept as small as possible to prevent over-fitting and to make the model efficiently computable. Based on these conditions, genetic programming is employed for the generation and selection of the appropriate basis. Since the obtained model can be expressed in simple mathematical expressions, it is suitable for using the model as a macro or behavior model in system level simulation. Experimental results are shown.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1587/e81-a_5_924/_p

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@ARTICLE{e81-a_5_924,
author={Sermsak UATRONGJIT, Nobuo FUJII, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Application of Genetic Programming to System Modeling from Input-Output Data},
year={1998},
volume={E81-A},
number={5},
pages={924-930},
abstract={A new approach for generating a system model from its input-output data is presented. The model is approximated as a linear combination of simple basis functions. The number of basis functions is kept as small as possible to prevent over-fitting and to make the model efficiently computable. Based on these conditions, genetic programming is employed for the generation and selection of the appropriate basis. Since the obtained model can be expressed in simple mathematical expressions, it is suitable for using the model as a macro or behavior model in system level simulation. Experimental results are shown.},
keywords={},
doi={},
ISSN={},
month={May},}

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TY - JOUR
TI - Application of Genetic Programming to System Modeling from Input-Output Data
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 924
EP - 930
AU - Sermsak UATRONGJIT
AU - Nobuo FUJII
PY - 1998
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E81-A
IS - 5
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - May 1998
AB - A new approach for generating a system model from its input-output data is presented. The model is approximated as a linear combination of simple basis functions. The number of basis functions is kept as small as possible to prevent over-fitting and to make the model efficiently computable. Based on these conditions, genetic programming is employed for the generation and selection of the appropriate basis. Since the obtained model can be expressed in simple mathematical expressions, it is suitable for using the model as a macro or behavior model in system level simulation. Experimental results are shown.
ER -