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Volumn , Issue , 2011, Pages

GMDH Neural Networks

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[No Author keywords available]

Indexed keywords


EID: 85131501845     PISSN: None     EISSN: None     Source Type: Book    
DOI: None     Document Type: Chapter
Times cited : (2)

References (29)
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    • Confidence estimation of GMDH neural networks and its application in fault detection systems
    • J. Korbicz and M. Mrugalski, Confidence estimation of GMDH neural networks and its application in fault detection systems, International Journal of System Science, 39(8), 783-800, 2008.
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    • Korbicz, J.1    Mrugalski, M.2
  • 18
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    • D.W. Pearson, N.C. Steel, and R.F. Albrecht, Eds., Wien, New York: Springer-Verlag
    • M. Mrugalski, E. Arinton, and J. Korbicz, Systems identification with the GMDH neural networks:A multi-dimensional case, in Computer Science: Artificial Neural Nets and Genetic Algorithms, D.W. Pearson, N.C. Steel, and R.F. Albrecht, Eds., Wien, New York: Springer-Verlag, 2003.
    • (2003) Computer Science: Artificial Neural Nets and Genetic Algorithms
    • Mrugalski, M.1    Arinton, E.2    Korbicz, J.3
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    • Confidence estimation of the multi-layer perceptron and its application in fault detection systems
    • M. Mrugalski, M. Witczak, and J. Korbicz, Confidence estimation of the multi-layer perceptron and its application in fault detection systems, Engineering Applications of Artificial Intelligence, 21, 895-906, 2008.
    • (2008) Engineering Applications of Artificial Intelligence , vol.21 , pp. 895-906
    • Mrugalski, M.1    Witczak, M.2    Korbicz, J.3
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    • Combined computational intelligence and analytical methods in fault diagnosis
    • A.E. Ruano, Ed., London, U.K.: The Institution of Electrical Engineers, IEE
    • R.J. Patton, J. Korbicz, M. Witczak, and J.U. Faisel, Combined computational intelligence and analytical methods in fault diagnosis, in Intelligent Control Systems Using Computational Intelligence Techniques, A.E. Ruano, Ed., London, U.K.: The Institution of Electrical Engineers, IEE, pp. 349-392, 2005.
    • (2005) Intelligent Control Systems Using Computational Intelligence Techniques , pp. 349-392
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    • Advances in model-based fault diagnosis with evolutionary algorithms and neural networks
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    • A GMDH neural network based approach to robust fault detection and its application to solve the DAMADICS benchmark problem
    • M. Witczak, J. Korbicz, M. Mrugalski, and R.J. Patton, A GMDH neural network based approach to robust fault detection and its application to solve the DAMADICS benchmark problem, Control Engineering Practice, 14, 671-683, 2006.
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    • Witczak, M.1    Korbicz, J.2    Mrugalski, M.3    Patton, R.J.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.