DocumentCode :
467734
Title :
Research on Universal Fuzzy Neural Comprehensive Evaluation Network
Author :
Chen, Juan ; Lu, Bin
Author_Institution :
North China Electr. Power Univ., Baoding
Volume :
3
fYear :
2007
fDate :
19-22 Aug. 2007
Firstpage :
1254
Lastpage :
1259
Abstract :
It is a difficult problem to make a perfect comprehensive evaluation on the complex systems with subjectivity and fuzziness. To attain an authentic comprehensive evaluation result in reducing evaluation difficulties, a universal fuzzy comprehensive evaluation network is proposed, which integrates the theory of universal logics and neural networks to serve as a basis for constructing a comprehensive evaluation system with objective weights distribution, appropriate membership functions and adaptive fuzzy compound operators. The comprehensive evaluation network has a simple and intuitively understandable structure, and is not only used to tune the weights distribution and membership functions of fuzzy systems, but also used to tune the compound operators continuously. Its learning techniques can automate this process and substantially reduce development time and cost while improving performance. Therefore, it can be used to a wide range of complex comprehensive evaluation problems. Finally, the practical applications indicate the effectiveness of the proposed model.
Keywords :
fuzzy neural nets; fuzzy set theory; fuzzy systems; adaptive fuzzy compound operators; authentic comprehensive evaluation; complex systems; fuzzy systems; learning techniques; universal fuzzy neural comprehensive evaluation network; universal logics; Artificial neural networks; Concrete; Costs; Cybernetics; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Machine learning; Power generation economics; Power system economics; Complex System; Comprehensive Evaluation; Fuzzy Neural Network; Universal logics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
Type :
conf
DOI :
10.1109/ICMLC.2007.4370337
Filename :
4370337
Link To Document :
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