러프셋 이론을 이용한 신경망의 구조 최적화

Structure Optimization of Neural Networks using Rough Set Theory

  • 정영준 (로보틱스 및 지능정보시스템 연구실) ;
  • 이동욱 (중앙대학교 공과대학 제어계측공학과) ;
  • 심귀보 (중앙대학교 공과대학 제어계측공학과)
  • 발행 : 1998.03.01

초록

Neural Network has good performance in pattern classification, control and many other fields by learning ability. However, there is effective rule or systematic approach to determine optimal structure. In this paper, we propose a new method to find optimal structure of feed-forward multi-layer neural network as a kind of pruning method. That eliminating redundant elements of neural network. To find redundant elements we analysis error and weight changing with Rough Set Theory, in condition of executing back-propagation leaning algorithm.

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