Pareto RBF network ensemble using multi-objective evolutionary computation

  • Kondo, Nobuhiko (Department of Information and Physical Sciences, Graduate School of Information Science and Technology) ;
  • Hatanaka, Toshiharu (Department of Information and Physical Sciences, Graduate School of Information Science and Technology) ;
  • Uosaki, Katsuji (Department of Information and Physical Sciences, Graduate School of Information Science and Technology)
  • Published : 2005.06.02

Abstract

In this paper, evolutionary multi-objective selection method of RBF networks structure is considered. The candidates of RBF network structure are encoded into the chromosomes in GAs. Then, they evolve toward Pareto-optimal front defined by several objective functions concerning with model accuracy and model complexity. An ensemble network constructed by such Pareto-optimal models is also considered in this paper. Some numerical simulation results indicate that the ensemble network is much robust for the case of existence of outliers or lack of data, than one selected in the sense of information criteria.

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