DocumentCode :
2762169
Title :
Hierarchical fuzzy rule-based classification system by evolutionary boosting algorithm
Author :
Amouzadi, Azam ; Mirzaei, Abdolreza
Author_Institution :
Electr. & Comput. Eng. Dept., Isfahan Univ. of Technol., Isfahan, Iran
fYear :
2010
fDate :
4-6 Dec. 2010
Firstpage :
909
Lastpage :
913
Abstract :
In this paper, a new Hierarchical fuzzy classifier based on evolutionary boosting algorithms is proposed. The main goal of this paper is to improve the performance of fuzzy rule based classifiers through utilizing hierarchical structure for achieving fuzzy rules. The advantages of hierarchical fuzzy rules generated by evolutionary boosting algorithms are evaluated by comparison between the performance of proposed algorithm and other classifications methods on a set of standard classification tasks.
Keywords :
evolutionary computation; fuzzy set theory; knowledge based systems; pattern classification; evolutionary boosting algorithms; fuzzy rule based classification system; hierarchical fuzzy classifier; Accuracy; Algorithm design and analysis; Boosting; Classification algorithms; Gallium; Iris; Training; boosting algorithm; classification; evolutionary algorithm; hierarchical fuzzy rule;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Telecommunications (IST), 2010 5th International Symposium on
Conference_Location :
Tehran
Print_ISBN :
978-1-4244-8183-5
Type :
conf
DOI :
10.1109/ISTEL.2010.5734152
Filename :
5734152
Link To Document :
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