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| Using genetic algorithm based fuzzy adaptive resonance theory for clustering analysis | |
| 引用本文： | LIU Bo WANG Yong WANG Hong-jian. Using genetic algorithm based fuzzy adaptive resonance theory for clustering analysis[J]. 哈尔滨工程大学学报, 2006, 27(Z1): 547-551 |
| 作者姓名： | LIU Bo WANG Yong WANG Hong-jian |
| 作者单位： | 1. 重庆工商大学 2. 重庆教育学院 |
| 摘 要： | |
| 文章编号： | 1006-7043(2006)增-0547-05 |
| 修稿时间： | 2006-05-24 |
Using genetic algorithm based fuzzy adaptive resonance theory for clustering analysis |
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| LIU Bo,WANG Yong,WANG Hong-jian. Using genetic algorithm based fuzzy adaptive resonance theory for clustering analysis[J]. Journal of Harbin Engineering University, 2006, 27(Z1): 547-551 | |
| Authors: | LIU Bo WANG Yong WANG Hong-jian |
| Abstract: | In the clustering applications field, fuzzy adaptive resonance theory system has been widely applied. But, three parameters of fuzzy adaptive resonance theory need to be adjusted manually for obtaining better clustering. It needs much time to test and does not assure a best result. Genetic algorithm is an optimal mathematical search technique based on the principles of natural selection and genetic recombination. So, to make the fuzzy adaptive resonance theory parameters choosing process automation, an approach incorporating genetic algorithm and fuzzy adaptive resonance theory neural network has been applied. Then, the best clustering result can be obtained.Through experiment, it can be proved that the most appropriate parameters of fuzzy adaptive resonance theory can be gained effectively by this approach. |
| Keywords: | clustering analysis genetic algorithm fuzzy adaptive resonance theory artificial neural networks |
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