An improved FCMBP fuzzy clustering method based on evolutionary programming
An improved FCMBP fuzzy clustering method based on evolutionary programming
复制标题
基于进化规划的改进FCMBP模糊聚类方法
DOI：
10.1016/j.camwa.2010.12.063
复制
发表时间：
2011-02
期刊：
影响因子：
--
通讯作者：
Lee, E. S.
中科院分区：
文献类型：
--
作者：
Tan, Qing;He, Qing;Zhao, Weizhong;Shi, Zhongzhi;Lee, E. S.
在目前的PC机计算环境下，基于扰动的模糊聚类方法（FCMBP）在处理阶数大于10的相似矩阵时失效。这是因为FCMBP中采用的遍历过程是指数级复杂度。把寻求具有最小"失真"的最优模糊等价矩阵看作优化问题 来求解,提出了一种基于进化规划的FCMBP模糊聚类改进方法.该方法通过对候选解进行多代进化，寻找与给定模糊相似矩阵最接近的最优模糊等价矩阵。通过使用变异算子从现有种群形成新的种群。最后，通过求解得到全局最优的模糊等价矩阵，或者近似得到全局最优的模糊等价矩阵。与FCMBP算法相比，改进算法具有以下优点：（1）引入基于进化规划的优化技术，避免了遍历搜索。(2)对于低阶矩阵，该方法在寻找全局最优模糊等价矩阵方面具有更好的效率。(3)可以管理具有数百个订单的矩阵。与传递闭包法相比，该方法可以快速得到更精确的解，并且通过进一步的迭代可以达到更高的精度要求。并且该方法适用于高阶矩阵。(4)该方法具有耐用性，对参数不敏感。
In current PC computing environment, the fuzzy clustering method based on perturbation (FCMBP) is failed when dealing with similar matrices whose orders are higher than tens. The reason is that the traversal process adopted in FCMBP is exponential complexity. This paper treated the process of finding fuzzy equivalent matrices with smallest error from an optimization point of view and proposed an improved FCMBP fuzzy clustering method based on evolutionary programming. The method seeks the optimal fuzzy equivalent matrix which is nearest to the given fuzzy similar matrix by evolving a population of candidate solutions over a number of generations. A new population is formed from an existing population through the use of a mutation operator. Better solutions survive into next generation and finally the globally optimal fuzzy equivalent matrix could be obtained or approximately obtained. Compared with FCMBP, the improved method has the following advantages: (1) Traversal searching is avoided by introducing an evolutionary programming based optimization technique. (2) For low-order matrices, the method has much better efficiency in finding the globally optimal fuzzy equivalent matrix. (3) Matrices with hundreds of orders could be managed. The method could quickly get a more accurate solution than that obtained by the transitive closure method and higher precision requirement could be achieved by further iterations. And the method is adaptable for matrices of higher order. (4) The method is robust and not sensitive to parameters.
登录
查看更多内容
DOI：
10.1109/icmlc.2004.1380654
发表时间：
2004-08
期刊：
Proceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826)
影响因子：
--
作者：
Wei Gao
通讯作者：
Wei Gao
DOI：
--
发表时间：
1999
期刊：
Fuzzy systems and mathematics
影响因子：
--
作者：
L. Hong
通讯作者：
L. Hong
DOI：
--
发表时间：
2007
期刊：
Journal of Anhui Agricultural Sciences
影响因子：
--
作者：
Liao Yan-ling
通讯作者：
Liao Yan-ling
DOI：
10.1016/0031-3203(90)90087-2
发表时间：
1990-11
期刊：
Pattern Recognit.
影响因子：
--
作者：
R. Wilson;M. Spann
通讯作者：
R. Wilson;M. Spann
影响因子：
3.9
作者：
LI, HX
通讯作者：
LI, HX