| 引用本文: | 张永,吴晓蓓,向峥嵘,胡维礼.复杂模糊分类系统的协同进化设计方法[J].控制理论与应用,2007,24(1):32~38.[点击复制] |
| ZHANG Yong, WU Xiao-bei, XIANG Zheng-rong, HU Wei-li.Design of complex fuzzy classificationsystem based on cooperative coevolutionary algorithm[J].Control Theory and Technology,2007,24(1):32~38.[点击复制] |
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| 复杂模糊分类系统的协同进化设计方法 |
| Design of complex fuzzy classificationsystem based on cooperative coevolutionary algorithm |
| 摘要点击 1583 全文点击 1357 投稿时间：2005-09-02 修订日期：2006-02-23 |
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| DOI编号 10.7641/j.issn.1000-8152.2007.1.006 |
| 2007,24(1):32-38 |
| 中文关键词 模糊分类系统 特征变量选择 协同进化算法 解释性 |
| 英文关键词 fuzzy classification systems feature selection fuzzy clustering co-evolution algorithm interpretability |
| 基金项目 国家自然科学资助项目 60474034 |
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| 中文摘要 |
| 提出一种基于协同进化算法的复杂模糊分类系统的设计方法.
该方法由以下3步组成: 1)利用Simba算法进行特征变量选择;
2)采用模糊聚类算法辨识初始的模糊模型;
3)利用协同进化算法对所获得的初始模糊模型进行结构和参数的优化.
协同进化算法由三类种群组成; 规则数种群, 规则前件种群和隶属函数种群;
其适应度函数同时考虑模型的精确性和解释性,
采用三类种群合作计算的策略. 利用该方法对多个典型问题进行分类,
仿真结果验证了方法的有效性. |
| 英文摘要 |
| A novel approach to construct complex fuzzy
classification system based on cooperative
coevolutionary(Co-evolution) algorithm is proposed in this paper.
The approach is composed of three phases: 1)~feature selection is
accomplished by the Simba algorithm; 2)~the initial fuzzy system is
identified using the fuzzy clustering algorithm; 3)~the structure
and parameters of the fuzzy system are optimized by the Co-evolution
algorithm. The Co-evolution algorithm owns three species including
the number of fuzzy rules species, the premise structure species and
the parameters species. Considering both precision and
interpretability, the fitness function is calculated on the
cooperation of individuals from the three species. The proposed
approach had been applied to several benchmark problems, the results
showed its validity. |
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