Using the bees algorithm with Kalman filtering to train an artificial neural network for pattern classification

被引：18

作者：

Pham, D. T. ^{[1
]}

Darwish, A. Haj ^{[1
]}

机构：

[1] Cardiff Univ, Mfg Engn Ctr, Cardiff CF24 3AA, S Glam, Wales

来源：

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING | 2010年 / 224卷 / I7期

关键词：

bees algorithm; fuzzy logic; Kalman filter; neural network; pattern classification; DESIGN;

D O I：

10.1243/09596518JSCE1004

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The current paper presents the use of the bees algorithm with Kalman filtering to train a radial basis function (RBF) neural network. An enhanced fuzzy selection system has been developed to choose local search sites depending on the error and training accuracy of the RBF network. The paper provides comparative results obtained when applying RBF neural classifiers trained using the new bees algorithm, the original bees algorithm, and the conventional RBF procedure to an industrial pattern classification problem.

引用

页码：885 / 892

页数：8

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