Design of Gas Identification System with Hierarchical Rule base using Genetic Algorithms and Rough Sets

유전 알고리즘과 러프 집합을 이용한 계층적 식별 규칙을 갖는 가스 식별 시스템의 설계

  • 방영근 (강원대학교 신재생에너지 연구소) ;
  • 변형기 (강원대학교 전자 정보통신공학부) ;
  • 이철희 (강원대학교 전기전자공학과)
  • Received : 2012.03.02
  • Accepted : 2012.07.24
  • Published : 2012.08.01


Recently, machine olfactory systems as an artificial substitute of the human olfactory system are being studied actively because they can scent dangerous gases and identify the type of gases in contamination areas instead of the human. In this paper, we present an effective design method for the gas identification system. Even though dimensionality reduction is the very important part, in pattern analysis, We handled effectively the dimensionality reduction by grouping the sensors of which the measured patterns are similar each other, where genetic algorithms were used for combination optimization. To identify the gas type, we constructed the hierarchical rule base with two frames by using rough set theory. The first frame is to accept measurement characteristics of each sensor and the other one is to reflect the identification patterns of each group. Thus, the proposed methods was able to accomplish effectively dimensionality reduction as well as accurate gas identification. In simulation, we demonstrated the effectiveness of the proposed methods by identifying five types of gases.


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