A rough set based fuzzy neural network algorithm for weather prediction

Kan Li*, Yu Shu Liu

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

14 引用 (Scopus)

摘要

A rough set based fuzzy neural network algorithm is proposed to solve weather prediction. In order to avoid arriving at local minimum value, the least square algorithm (LSA) is used in the learning process of fuzzy neural network to obtain global convergence. Because structure of fuzzy neural networks, the numbers of rules and the initial weights are difficult to be determined, here the rough sets method is introduced to decide the numbers of rules and original weights. Finally, the proposed algorithm through standard data set is testified to have better rationality and availability than BP algorithm. Experiment results show the algorithm for weather prediction may get better effect.

源语言英语
主期刊名2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005
1888-1892
页数5
出版状态已出版 - 2005
活动International Conference on Machine Learning and Cybernetics, ICMLC 2005 - Guangzhou, 中国
期限: 18 8月 200521 8月 2005

出版系列

姓名2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005

会议

会议International Conference on Machine Learning and Cybernetics, ICMLC 2005
国家/地区中国
Guangzhou
时期18/08/0521/08/05

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