An improved fuzzy comprehensive evaluation using expanded optimization algorithm for combining index weights

doi:10.1109/ICMLC.2008.4620454

	An improved fuzzy comprehensive evaluation using expanded optimization algorithm for combining index weights
	Chen, Wei; Hao, Xiao-Hong; Lin, Jie
	2008
会议日期	July 12, 2008 - July 15, 2008
会议地点	Kunming, China
关键词	Machine learning Maximum principle Optimization Surface discharges Degree of membership Fuzzy comprehensive evaluation Fuzzy comprehensive evaluation method Matrix of fuzzy relations Maximum degree Optimization algorithms Sequential segmentation Weight vector
卷号	1
DOI	10.1109/ICMLC.2008.4620454
页码	490-494
英文摘要	Fuzzy Comprehensive evaluation is usually influenced significantly by the matrix of fuzzy relation and weight vector. For a sequential segmentation category, the principle of the lowest cost, the principle of maximum degree of measure and the principle of maximum degree of membership sometimes can get unreasonable conclusion, because they conceal the difference of two degree of membership. First of all, a new expanded optimization algorithm is presented for combining index weights, then bring out a improved fuzzy Comprehensive evaluation method based on reliability code. The proposed method can overcome the shortages of the traditional fuzzy Comprehensive evaluation. Case results clearly show that the proposed method is attractive and effective. © 2008 IEEE.
会议录	Proceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC
会议录出版者	IEEE Computer Society
语种	英语
内容类型	会议论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/116879]
专题	电气工程与信息工程学院
作者单位	College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China
推荐引用方式 GB/T 7714	Chen, Wei,Hao, Xiao-Hong,Lin, Jie. An improved fuzzy comprehensive evaluation using expanded optimization algorithm for combining index weights[C]. 见:. Kunming, China. July 12, 2008 - July 15, 2008.