| 一类基于数据的解释性模糊建模方法的研究 |
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| 引用本文： | 邢宗义,贾利民,张永,胡维礼,秦勇.一类基于数据的解释性模糊建模方法的研究[J].自动化学报,2005,31(6):815-824. |
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| 作者姓名： | 邢宗义 贾利民 张永 胡维礼 秦勇 |
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| 作者单位： | 1.Automation Department, Nanjing University of Science and Technology, Nanjing 210094 |
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| 基金项目： | Supported by National Natural Science Foundation of P.R.China (60332020) and Scientific Research Foundation of Nanjing University of Science and Technology (2005) |
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| 摘 要： | An approach to identify interpretable fuzzy models from data is proposed. Interpretability, which is one of the most important features of fuzzy models, is analyzed first. The number of fuzzy rules is determined by fuzzy cluster validity indices. A modified fuzzy clustering algorithm,combined with the least square method, is used to identify the initial fuzzy model. An orthogonal least square algorithm and a method of merging similar fuzzy sets are then used to remove the redundancy of the fuzzy model and improve its interpretability. Next, in order to attain high accuracy, while preserving interpretability, a constrained Levenberg-Marquardt method is utilized to optimize the precision of the fuzzy model. Finally, the proposed approach is applied to a PH neutralization process, and the results show its validity.
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| 关 键 词： | Fuzzy modeling interpretability fuzzy clustering |
| 收稿时间： | 2004-07-27 |
| 修稿时间： | 2004年7月27日 |
A Case Study of Data-driven Interpretable Fuzzy Modeling |
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| XING Zong-Yi,JIA Li-Min,ZHANG Yong,HU Wei-Li,QIN Yong.A Case Study of Data-driven Interpretable Fuzzy Modeling[J].Acta Automatica Sinica,2005,31(6):815-824. |
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| Authors: | XING Zong-Yi JIA Li-Min ZHANG Yong HU Wei-Li QIN Yong |
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| Affiliation: | 1.Automation Department, Nanjing University of Science and Technology, Nanjing 210094 |
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| Abstract: | An approach to identify interpretable fuzzy models from data is proposed.Interpretabil- ity,which is one of the most important features of fuzzy models,is analyzed first.The number of fuzzy rules is determined by fuzzy cluster validity indices.A modified fuzzy clustering algorithm, combined with the least square method,is used to identify the initial fuzzy model.An orthogonal least square algorithm and a method of merging similar fuzzy sets are then used to remove the re- dundancy of the fuzzy model and improve its interpretability.Next,in order to attain high accuracy, while preserving interpretability,a constrained Levenberg-Marquardt method is utilized to optimize the precision of the fuzzy model.Finally,the proposed approach is applied to a PH neutralization process,and the results show its validity. |
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| Keywords: | Fuzzy modeling interpretability fuzzy clustering |
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