A New Fuzzy MADM Method: Fuzzy RBF Neural Network Model

  • Hongyan Liu
  • Feng Kong
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4223)


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.


Hide Unit Fuzzy Triangular Number Relatively Good Wavelet Neural Network Negative Ideal Solution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Li, R.-J.: Fuzzy Multi-attribute Decision Making Theory and Its applications. Science Press, Beijing (2002)Google Scholar
  2. 2.
    Song, R.: Multi-attribute Decision Making Method Based on Wavelet Neural Networks. Computer Engineering and Applications 35, 46–48 (2000)Google Scholar
  3. 3.
    Qiu, C., Liu, Y.: Multi-attribute Decision Making Based on Artificial Neural Network. Journal of Beijing Science and Engineering University 20, 65–68 (2000)Google Scholar
  4. 4.
    Hdgan, M.T., Demuth, H.B., Beale, M.: Neural Network Design. PWS Publishing Company (1996)Google Scholar
  5. 5.
    Song, G., Zou, P.: Weight Determination in Multi-attribute Decision Making. Systems Engineering 19, 84–89 (2001)Google Scholar
  6. 6.
    Fuller, R., Carlsson, C.: Fuzzy Multiple Criteria Decision Making: Recent Development. Fuzzy sets and Fuzzy systems 78, 139–153 (1996)MATHCrossRefMathSciNetGoogle Scholar
  7. 7.
    Jie, L., Hou, Z.: Weight Determination Method Based on a Combination of AHP, Delphi method and Neural Network. Systems Engineering Theories and Practices 20, 59–63 (2001)Google Scholar
  8. 8.
    Herrera, F., Herrera, E.: Linguistic decision analysis: steps for solving decision problems under linguistic information. Fuzzy Sets and Systems 115, 67–82 (2000)MATHCrossRefMathSciNetGoogle Scholar
  9. 9.
    Cheng, C.-H., Lin, Y.: Evaluating the best main battle tank using fuzzy decision theory with linguistic criteria evaluation. European Journal of Operational Research 142, 174–186 (2002)MATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Hongyan Liu
    • 1
  • Feng Kong
    • 1
  1. 1.North China Electric Power UniversityBaodingP.R. China

Personalised recommendations