Development of Comfort Feeling Structure in Indoor Environments Using Hybrid Neuralnetworks

하이브리드 신경망을 이용한 실내(室內) 쾌적감성(快適感性)모형 개발

  • 전용웅 (동국대학교 산업공학과) ;
  • 조암 (동국대학교 정보산업대학 산업시스템공학부)
  • Received : 2000.12.11
  • Accepted : 2001.07.25
  • Published : 2001.08.31

Abstract

This study is about the modeling of comfort feeling structure in indoor environments. To represent the degree of practical comfort feeling level in an environment, we measured elements of human sense and resultant elements of comfort feeling such as coziness, refreshment, and freshness with physical values(temperature, illumination, noise. etc.). The relationships of elements of human sense and elements of comfort feeling were formulated as a fuzzy model. And a hybrid-neural network with three layers were designed where obtained from fuzzy membership function values of the elements of human sense were used as inputs, and given as fuzzy membership function values of resultant elements of comfort feeling were used as outputs. Both kinds of fuzzy membership function values were obtained from physical values. The network was trained by measured data set. The proposed hybrid-neural network were tested and proposed a more realistic model of comfort feeling structure in indoor environments.

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Acknowledgement

Supported by : 동국대학교