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Forecasting Of Type-2 Fuzzy Electric Power System Based On Phase Space Reconstruction Model
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- 발행기관
- 보안공학연구지원센터(IJGDC) 바로가기
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- 간행물
- International Journal of Grid and Distributed Computing 바로가기
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- 통권
- Vol.8 No.5 (2015.10)바로가기
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- 페이지
- pp.263-272
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- 저자
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- 언어
- 영어(ENG)
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- URL
- https://www.earticle.net/Article/A257205
※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.
원문정보
초록
- 영어
- Type-2 fuzzy logic to make up for the lack of a type of fuzzy logic in dealing with uncertainty, object contains uncertainty is strong; the application of type-2 fuzzy logic advantage is more obvious. In this paper, type-2s of fuzzy logic for power load time series forecasting, good results were obtained. According to the power load has strong randomness it is difficult to accurately forecast problem, the introduction of the type-2 of fuzzy logic in order to reduce the prediction error. According to the power load is difficult to predict accurately the problem, this paper introduces the interval type-2 fuzzy logic method to reduce the prediction error, presents an interval type-2 fuzzy logic model for the time series of one hour of power load forecasting, and adopted the first modeling process model structure, and then use back propagation algorithm to adjust the model parameters are determined by simulation. At the same time, based on the back-propagation algorithm of a fuzzy model with interval type-2 fuzzy model, singular value decomposition iterative blending algorithm of interval type-2 fuzzy model, the predicted result was the test performance benchmark. The simulation results show that the prediction accuracy of the forecasting model, based on the established with high, can better track the actual load curve, a better performance than the other three models.
목차
Abstract
1. Introduction
2. Related Work
2.1. Type-2 Fuzzy Sets
2.2. Triangle Type-2 Fuzzy Logic System
2.3. The Shortcoming of the Current Type-2 Fuzzy Sets Theory
3. The Type-2 of Fuzzy System Rule Base Simplification Algorithm
3.1. Interval Type-2 Fuzzy Similarity
3.2. SVD-SM-BP Hybrid Iterative Algorithm
3.3. Type-2 Fuzzy Logic System
4. Experimental Results
4.1. The Simulation and Verification
4.2. Design of the Prediction Model of Type-2 Fuzzy
5. Conclusions
Acknowledgement
References
키워드
Type-2 fuzzy sets forecasting reconstruction similarity measure저자
간행물 정보
발행기관
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- 발행기관명
- 보안공학연구지원센터(IJGDC) [Science & Engineering Research Support Center, Republic of Korea(IJGDC)]
- 설립연도
- 2006
- 분야
- 공학>컴퓨터학
- 소개
- 1. 보안공학에 대한 각종 조사 및 연구 2. 보안공학에 대한 응용기술 연구 및 발표 3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최 4. 보안공학 기술의 상호 협조 및 정보교환 5. 보안공학에 관한 표준화 사업 및 규격의 제정 6. 보안공학에 관한 산학연 협동의 증진 7. 국제적 학술 교류 및 기술 협력 8. 보안공학에 관한 논문지 발간 9. 기타 본 회 목적 달성에 필요한 사업
간행물
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- 간행물명
- International Journal of Grid and Distributed Computing
- 간기
- 격월간
- pISSN
- 2005-4262
- 수록기간
- 2008~2016
- 십진분류
- KDC 505 DDC 605
이 권호 내 다른 논문 / International Journal of Grid and Distributed Computing Vol.8 No.5
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