引用本文: | 李 柠,李少远,席裕庚.基于满意聚类的多模型建模方法[J].控制理论与应用,2003,20(5):783~787.[点击复制] |
LI Ning,LI Shao-yuan,XI Yu-geng.Multi-model modeling method based on satisfactory clustering[J].Control Theory and Technology,2003,20(5):783~787.[点击复制] |
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基于满意聚类的多模型建模方法 |
Multi-model modeling method based on satisfactory clustering |
摘要点击 2184 全文点击 1596 投稿时间:2001-05-14 修订日期:2002-03-28 |
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DOI编号 10.7641/j.issn.1000-8152.2003.5.028 |
2003,20(5):783-787 |
中文关键词 多模型 Gustafson-Kessel模糊聚类(GK) 满意聚类 |
英文关键词 multi-model Gustafson-Kessel fuzzy clustering (GK) satisfactory clustering |
基金项目 国家自然科学基金(69934020;60074004)资助项目 |
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中文摘要 |
从系统输入输出数据出发, 首先在GK模糊聚类算法的基础上, 提出一种模糊满意聚类算法, 该算法能快速对系统进行用户满意的模糊划分 ;继而将其引入多模型建模过程中, 满意的系统划分数目即对应多模型个数, 然后针对不同的聚类建立起相应的子系统模型, 全局系统可视为各子模型的加权组合 ;最后通过几个典型实例验证了模糊满意聚类及基于此的多模型建模方法的有效性、准确性和快速性. |
英文摘要 |
First of all, from input-output data set, a satisfactory clustering algorithm based on GK fuzzy clustering was presented. Using this algorithm, a system could be quickly divided into multiple optimal fuzzy parts. Then the algorithm was used in multi-model modeling process. Satisfactory cluster number corresponded to the optimal number of sub-systems. For multiple clusters, multiple models could then be built, and the global system was described as their certain combination. Finally, examples are given to prove the effectiveness of the method. |
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