Hopfield Neural Network Modeling Method Based on Subset KPCA with FCMC Clustering

被引：0

作者：

Luo, Xiang-Jie ^{[1
]}

Li, Xiao-Yong ^{[2
]}

Qu, Hong ^{[2
]}

Meng, Yue-Bo ^{[3
]}

机构：

[1] XiJing Coll, Xian 710123, Shaanxi, Peoples R China

[2] Air Force Engn Univ, Air Traff Control & Nav Coll, Xian 710051, Shaanxi, Peoples R China

[3] Xi An Jiao Tong Univ, Syst Engn Inst, Xian 710049, Shaanxi, Peoples R China

来源：

MODERN TECHNOLOGIES IN MATERIALS, MECHANICS AND INTELLIGENT SYSTEMS | 2014年 / 1049卷

关键词：

Hopfield Neural Network; Subset KPCA; FCMC Clustering; Flight Parameters;

D O I：

10.4028/www.scientific.net/AMR.1049-1050.1658

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

In order to improve the performance of nonlinear modeling, a Hopfield neural network modeling method based on Subset Kernel Principal Components Analysis (SubKPCA) with Fuzzy C-Means Clustering (FCMC) is proposed. The simulation result shows that, the performance of the proposed method is better than that of Hopfield neural network based on KPCA. It also is effective and feasible to establish the model for the estimation of missing flight data.

引用

页码：1658 / +

页数：2

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