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一类基于数据的解释性模糊建模方法的研究

邢宗义 贾利民 张永 胡维礼 秦勇

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. 自动化学报, 2005, 31(6): 815-824.
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. 自动化学报, 2005, 31(6): 815-824.
XING Zong-Yi, JIA Li-Min, ZHANG Yong, HU Wei-Li, QIN Yong. A Case Study of Data-driven Interpretable Fuzzy Modeling. ACTA AUTOMATICA SINICA, 2005, 31(6): 815-824.
Citation: XING Zong-Yi, JIA Li-Min, ZHANG Yong, HU Wei-Li, QIN Yong. A Case Study of Data-driven Interpretable Fuzzy Modeling. ACTA AUTOMATICA SINICA, 2005, 31(6): 815-824.

一类基于数据的解释性模糊建模方法的研究

详细信息
    通讯作者:

    邢宗义

A Case Study of Data-driven Interpretable Fuzzy Modeling

More Information
    Corresponding author: XING Zong-Yi
  • 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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出版历程
  • 收稿日期:  2004-07-27
  • 修回日期:  2005-07-18
  • 刊出日期:  2005-11-20

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