Earticle

초록

영어

In this paper, adjust the system parameters back-propagation algorithm based on fuzzy similarity interval type proposed by the fuzzy rule base to streamline redundant fuzzy sets, we can also merge with the means to reduce the number of redundant fuzzy rules, then singular value decomposition method is preferred fuzzy rules. The algorithm can effectively eliminate the adverse effects caused by redundant fuzzy rule, which improve the interpretability of fuzzy rules to reduce the computational complexity of the fuzzy reasoning process, and to improve the approximation accuracy of the system. Based on the long-term and short-term load power load characteristics analysis, to identify the influence of the load itself changes and related factors, gray system theory, neural network model and chaotic time series methods, models and methods for forecasting power load range were research. Examples verified, interval prediction has better precision, demonstrate the effectiveness of the interval prediction algorithm, the research results can be used in power market analysis and forecasting systems, power system operation and provide scientific basis for management decisions.

목차

Abstract
 1. Introduction
 2. The Related Theory
  2.1 Research Status of Fuzzy Systems
  2.2 Load Forecasting Issues to Consider
 3. Type Two Fuzzy Logic Theory
  3.1 Interval Type Two Fuzzy Similarity
  3.2 Error Analysis Based on Grey Theory
  3.3 Long Term Load Forecasting Model Range
 4. The Experiment and Analysis
  4.1 Prediction Analysis
  4.2 Calculation Examples
 5. Conclusion
 Acknowledgments
 References

키워드

저자

• Qihui Wang [ Qianjiang College, Hangzhou Normal University, Hangzhou, 310036, China ]
• Yuhuai Wang [ Qianjiang College, Hangzhou Normal University, Hangzhou, 310036, China ] Corresponding author
• Huixi Zhang [ Qianjiang College, Hangzhou Normal University, Hangzhou, 310036, China ]
• Yaping Sun [ Qianjiang College, Hangzhou Normal University, Hangzhou, 310036, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605