Research on data mining algorithm based on neural network and particle swarm optimization

被引:9
作者
Fei, Xianju [1 ]
Tian, Guozhong [1 ]
机构
[1] Changzhou Inst Technol, Sch Comp Informat & Engn, Changzhou, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
Neural network algorithm; particle swarm optimization algorithm; data mining algorithm;
D O I
10.3233/JIFS-169647
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In previous studies, due to the sparsity and chaos of distributed data, such a result would lead to a local convergence phenomenon by using PSO algorithm, resulting in low accuracy of data mining. So this time we proposed a data mining algorithm based on neural network and particle swarm optimization. At the beginning, we calculated the global kernel function of differentiated distributed data mining and mixed to build the mining decision model. The training error was used as the constraint condition of mining optimization to realized data optimization mining. The results showed that the differential distributed data mining with this algorithm has higher accuracy and stronger convergence.
引用
收藏
页码:2921 / 2926
页数:6
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