| Hybrid approach for fuzzy system design |
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| 作者姓名： | 李映 赵荣椿 张艳宁 焦李成 |
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| 基金项目： | This project was supported by the National Natural Science Foundation of China (60141002). |
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| 摘 要： | A hybrid approach for fuzzy system design based on clustering and a kind of neurofuzzy networks is proposed. An unsupervised clustering technique is firstly used to determine the number of if-then fuzzy rules and generate an initial fuzzy rule base from the given input-output data. Then, a class of neurofuzzy networks is constructed and its weights are tuned so that the obtained fuzzy rule base has a high accuracy. Finally, two examples of function approximation problems are given to illustrate the effectiveness of the proposed approach.
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Hybrid approach for fuzzy system design |
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| Abstract: | A hybrid approach for fuzzy system design based on clustering and a kind of neurofuzzy networks is proposed. An unsupervised clustering technique is firstly used to determine the number of if-then fuzzy rules and generate an initial fuzzy rule base from the given input-output data. Then, a class of neurofuzzy networks is constructed and its weights are tuned so that the obtained fuzzy rule base has a high accuracy. Finally, two examples of function approximation problems are given to illustrate the effectiveness of the proposed approach. |
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| Keywords: | Fuzzy systems design fuzzy rule base clustering neurofuzzy networks |
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