Radial Basis Function Neural Network Based on Ant Colony Clustering

摘要：

By introducing ant colony clustering algorithm into neural network of radial basis function for optimally clustering N objects into K clusters.Based on ant colony algorithm and its feature of parallel search optimum,and employs the global pheromone updating and the heuristic information to construct clustering solution.The rate of clustering is accelerated by increasing the utilization of the pheromone.The heuristic information is applied to improve the efficiency of the algorithm.Uniform crossover operator is used to further improve solutions discovered by ants.The experimental results demonstrate that the very encouraging results in terms of the quality of solution found and the precision to RBF-ACC is improved evidently.

关键词： Ant Colony Algorithm Clustering Radial Basis Function Neural Network Optimization Uniform Crossover

作者: Peng Tian Xianfang Wang Zhou Wu Feng Pan

作者单位: School of Information & Control Engineering,Jiangnan University,Wuxi,Jiangsu 214122,P.R.China School of Information & Control Engineering,Jiangnan University,Wuxi,Jiangsu 214122,P.R.China Henan

会议类型: 国际会议

会议名称: 2008年国际电子商务、工程及科学领域的分布式计算和应用学术研讨会(2008 International Symposium on Distributed Computing and Applications for Business Engineering and Science)

会议地点: 大连

会议语种:英文

页码: 698-702

在线出版日期: 2008-07-27（万方平台首次上网日期，不代表论文的发表时间）