HCBKA를 이용한 IntervalType-2퍼지 논리시스템 기반 예측 시스템 설계

• 영문명: Prediction System Design basedon An IntervalType-2Fuzzy LogicSystem using HCBKA
• 발행기관: 강원대학교 산업기술연구소
• 저자명: 방영근(Bang,Young-Keun) 이철희(Lee,Chul-Heui)
• 간행물 정보: 『산업기술연구』vol.30, 111~118쪽, 전체 8쪽
• 주제분류: 공학 > 공학일반
• 파일형태: PDF
• 발행일자: 2010.09.30

영문 초록

To improve the performance of the prediction system, the system should reflect well the uncertainty of nonlinear data. Thus, this paper presents multiple prediction systems based on Type-2 fuzzy sets. To construct each prediction system, an Interval Type-2TSK Fuzzy Logic System and difference data were used, because, in general, it has been known that the Type-2 Fuzzy Logic System can deal with the uncertainty of nonlinear data better than the Type-1Fuzzy Logic System, and the difference data can provide more steady information than that of original data. Also, to improve each rule base of the fuzzy prediction systems, the HCBKA (Hierarchical Correlation Based K-means clustering Algorithm) was applied because it can consider correlation ship and statistical characteristics between data at a time. Subsequently, to alleviate complexity of the proposed prediction system, a system selection method was used. Finally, this paper analyzed and compared the performances between the Type-1 prediction system and the Interval Type-2 prediction system using simulations of three typical time series examples.

목차

1. 서론

2. 차분 데이터의 생성

3. IntervalType-2TSK 퍼지 논리 시스템

4. 예측 시스템의 선택

5. 시뮬레이션

6. 결론

키워드

Type-2 퍼지 집합 IntervalType-2 TSK 퍼지 논리시스템 차분데이터 HCBKA 시계열 데이터 Type-2 fuzzy sets IntervalType-2 Fuzzy Logic System difference data HCBKA time series