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A New Fuzzy MADM Method: Fuzzy RBF Neural Network Model

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Fuzzy Systems and Knowledge Discovery (FSKD 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4223))

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Abstract

An RBF neural network model with fuzzy triangular numbers as inputs is set up to solve fuzzy multi-attribute decision making (MADM) problems. The model can determine the weights of attributes automatically so that weights are more objectively and accurately distributed. In this model, decision maker’s specific preferences are considered in the determination of weights. It is simple, and can give objective results while taking into decision maker’s subjective intensions. A numerical example is given to illustrate the method.

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Author information

Authors and Affiliations

  1. North China Electric Power University, Baoding, 071003, P.R. China

    Hongyan Liu & Feng Kong

Authors
  1. Hongyan Liu
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  2. Feng Kong
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Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University,, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  2. Life Science Research Center, School of Electronic Engineering, Xidian University,, 710071, Xi’an, Shaanxi, China

    Licheng Jiao

  3. School of Electrical and Electronic Engineering, Xidian University, 710071, Xi’an, China

    Guanming Shi

  4. School of Information Technology and Electrical Engineering, The University of Queensland, 4072, Brisbane, Queensland, Australia

    Xue Li

  5. College of Mathematics and Information Science, Hebei Normal University, 050016, Shijiazhuang, Hebei, P.R. China

    Jing Liu

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© 2006 Springer-Verlag Berlin Heidelberg

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Liu, H., Kong, F. (2006). A New Fuzzy MADM Method: Fuzzy RBF Neural Network Model. In: Wang, L., Jiao, L., Shi, G., Li, X., Liu, J. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2006. Lecture Notes in Computer Science(), vol 4223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881599_118

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  • DOI: https://doi.org/10.1007/11881599_118

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-45916-3

  • Online ISBN: 978-3-540-45917-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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