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Performance of MGMDH Network on Structural Piecewise System Identification

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Intelligent Problem Solving. Methodologies and Approaches (IEA/AIE 2000)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1821))

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Abstract

This paper will address the capability of the Modified Group Method of Data Handling (MGMDH) for continuous and piecewise continuous approximation functions. The MGMDH is used to construct the mathematical structure of dynamic system, which is observable only from its input and output with large number of input variables. The paper present the theory and simulation results for estimation of piecewise continuous polynomial function. The output performance evaluation is included.

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Author information

Authors and Affiliations

  1. Computer Science, McNeese State University, Lake Charles, Louisiana, 70609

    Ali K. Setoodehnia

  2. Conoco, Lake Charles, Louisiana, 70601

    Hong Li

Authors
  1. Ali K. Setoodehnia
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  2. Hong Li
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Editor information

Editors and Affiliations

  1. The Center for Advanced Computer Studies, University of Lousiana, 2 Rex Street, Lafayette, LA, 70504-4330, USA

    Rasiah Logananthara

  2. Department of Neural Information Processing, University of Ulm, Oberer Eselsberg, 89069, Ulm, Germany

    Günther Palm

  3. Department of Computer Science, Southwest Texas State University, 601 University Drive, San Marcos, TX, 78666-4616, USA

    Moonis Ali

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© 2000 Springer-Verlag Berlin Heidelberg

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Setoodehnia, A.K., Li, H. (2000). Performance of MGMDH Network on Structural Piecewise System Identification. In: Logananthara, R., Palm, G., Ali, M. (eds) Intelligent Problem Solving. Methodologies and Approaches. IEA/AIE 2000. Lecture Notes in Computer Science(), vol 1821. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45049-1_89

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  • DOI: https://doi.org/10.1007/3-540-45049-1_89

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67689-8

  • Online ISBN: 978-3-540-45049-8

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