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BGNN Neural Network Based on Improved E.Coli Foraging Optimization Algorithm Used in the Nonlinear Modeling of Hydraulic Turbine

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Advances in Neural Networks – ISNN 2009 (ISNN 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5551))

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Abstract

A novel Bayesian-Gaussian neural network (BGNN) is proposed in this paper for the nonlinear modeling of hydraulic turbine which is difficult to obtain its mathematical model because of its complex and nonlinear characteristics. The topology and connection weights of BGNN can be set immediately when the training samples are available. The threshold matrix parameters of BGNN are updating based an improved E.Coli foraging optimization algorithm (IEFOA) which is an evolutionary optimization algorithm imitating the behaviors of E.Coli bacteria. Simulation results for the nonlinear model of hydraulic turbine generating unit are provided and demonstrate the effectiveness and shorter training time and more effective self-tuning compared with the BP neural network for the identification of hydraulic turbine generating unit.

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Authors and Affiliations

  1. School of Electrical & Automation Engineering, Nanjing Normal University, Nanjing, 210042, China

    Yijian Liu

  2. Department of Automation, Wuhan University, Wuhan, 430072, China

    Yijian Liu & Yanjun Fang

Authors
  1. Yijian Liu
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  2. Yanjun Fang
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Editor information

Editors and Affiliations

  1. Departamento de Control Automático, CINVESTAV-IPN, A.P. 14-740, Av.IPN 2508, 07360, México D.F., México

    Wen Yu

  2. Deptartment of Electrical and Computer Engineering, Stevens Institute of Technology, NJ 07030, Hoboken, USA

    Haibo He

  3. Dept. of Electrical and Computer Engineering, South Dakota School of Mines & Technology, 501 E. St. Joseph Street, Rapid City, SD 57701, USA

    Nian Zhang

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© 2009 Springer-Verlag Berlin Heidelberg

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Liu, Y., Fang, Y. (2009). BGNN Neural Network Based on Improved E.Coli Foraging Optimization Algorithm Used in the Nonlinear Modeling of Hydraulic Turbine. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5551. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01507-6_71

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  • DOI: https://doi.org/10.1007/978-3-642-01507-6_71

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01506-9

  • Online ISBN: 978-3-642-01507-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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