A Multi-Stage 75 K Fuzzy Modeling Method by Genetic Programming

  • Li Bo (Department of Industrial Engineering, Pusan National University, School of Management, Tianjin University) ;
  • Cho Kyu-Kab (Department of Industrial Engineering, Pusan National University)
  • Published : 2002.05.01

Abstract

This paper deals with a multi-stage TSK fuzzy modeling method by using Genetic Programming (GP). Based on the time sequence of sampling data the best structural change points of complex systems are detemined by using GP, and also the moving window is simultaneously introduced to overcome the excessive amount of calculation during the generating procedure of GP tree. Therefore, a multi-stage TSK fuzzy model that attempts to represent a complex problem by decomposing it into multi-stage sub-problems is addressed and its learning algorithm is proposed based on the Radial Basis Function (RBF) network. This approach allows us to determine the model structure and parameters by stages so that the problems ran be simplified.

Keywords