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New Results on Fuzzy Regression by Using Genetic Programming

  • Wolfgang Golubski
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2278)

Abstract

In this paper we continue the work on symbolic fuzzy regression problems. That means that we are interested in finding a fuzzy function f, which best matches given data pairs (X i,Y i ) 1 ≤ik of fuzzy numbers. We use a genetic programming approach for finding a suitable fuzzy function and will present test results about linear, quadratic and cubic fuzzy functions.

Keywords

Evolutionary Algorithm Fuzzy Number Genetic Programming Triangular Fuzzy Number Fuzzy Function 
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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Wolfgang Golubski
    • 1
  1. 1.Department of Electrical Engineering and Computer ScienceUniversity of SiegenSiegenGermany

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