유전알고리즘과 러프집합을 이용한 계층적 식별 규칙을 갖는 가스 식별 시스템의 설계

• 영문명: Design of Gas Identification System with Hierarchically Identifiable Rule base using GAS and Rough Sets
• 발행기관: 강원대학교 산업기술연구소
• 저자명: 조해파(Zhao Haibo) 방영근(Bang, Young-Keun) 이철희(Lee, Chul-Heui)
• 간행물 정보: 『산업기술연구』vol.31, 37~43쪽, 전체 7쪽
• 주제분류: 공학 > 공학일반
• 파일형태: PDF
• 발행일자: 2011.09.30

영문 초록

In pattern analysis, dimensionality reduction and reasonable identification rule generation are very important parts. This paper performed 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, this paper constructed the hierarchically identifiable 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, this paper demonstrated the effectiveness of the proposed methods by identifying five types of gases

목차

1. 서론

2. 제안된 식별 시스템의 구조

3. 정규화 및 그룹화

4. 러프집합을 이용한 식별 규칙의 생성

4. 시뮬레이션

5. 결론

키워드

패턴 분석 차원 축소 유전알고리즘 러프집합 이론 pattern analysis dimensionality reduction genetic algorithms rough set theory