Proceedings of the Korean Institute of Intelligent Systems Conference (한국지능시스템학회:학술대회논문집)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Design and Implementation of the Quality Performance Improvement for Process System Using Neural Network

가공시스템에서 신경회로망을 이용한 품질의 성능 개선에 관한 설계 및 구현

  • 문희근 (한국 해양대학교 전자통신 공학과) ;
  • 김영탁 (한국 해양대학교 전자통신 공학과) ;
  • 김수정 (한국 해양대학교 전자통신 공학과) ;
  • 김관형 (동명정보대학교 컴퓨터공학과) ;
  • 탁한호 (진주산업대학교 전자공학과) ;
  • 이상배 (한국해양대학교 전자통신 공학과)
  • Published : 2002.12.01

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Abstract

In this paper, this system makes use of the analog sensor and converts the feature of fish analog signal when sensor is operating with CPU(80C196KC). Then, After signal processing, this feature Is classified a special feature and a outline of fish by using the neural network, one of the artificial intelligence scheme. This neural network classifies fish pattern of very simple and short calculation. This has linear activation function and the error backpropagation is used as a learning algorithm. And the neural network is learned in off-line process. Because an adaptation period of neural network is too long time when random initial weights are used, off-line learning Is induced to decrease the Progress time We confirmed this method has better performance than somewhat outdated machines.

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