Generating fuzzy rules by learning from examples

  title={Generating fuzzy rules by learning from examples},
  author={Li-Xin Wang and Jerry M. Mendel},
  journal={IEEE Trans. Systems, Man, and Cybernetics},
A general method is developed to generate fuzzy rules from numerical data. This new method consists of five steps: Step 1 divides the input and output spaces of the given numerical data into fuzzy regions; Step 2 generates fuzzy rules from the given data; Step 3 assigns a degree of each of the generated rules for the purpose of resolving conflicts among the generated rules; Step 4 creates a combined fuzzy rule base based on both the generated rules and linguistic rules of human experts; and… CONTINUE READING
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Li-Xin Wang received the B.S. and M.S. degrees from the Northwestern Polytechnical University, Xian, People’s Republic of China

  • M Cambridge
  • A MIT Press,
  • 1986

Currently he is Professor of Electrical EngineeringSystems at the University of Southern California in Los Angeles, and is Director of the Signal & Image Processing Institute

  • Astronautics Company
  • He was Chairman of the EE-Systems Department from…
  • 1984

S’59-A’61-M’72-F778) received the B.S. degree in mechanical engineering and the M.S. and Ph.D. degrees in electrical engineering from the Polytechnic Institute of Brooklyn, Brooklyn

  • Jerry M. Mendel
  • 1959

Nonlinear signal processing using neural networks : Prediction and system modeling

  • J. L. McClelland

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