郑州轻工业学院学报（自然科学版）2012，Vol.27Issue(3)：89-92,4.
基于智能优化型径向基神经网络的板形模式识别研究
Study on flatness pattern recognition based on intelligent optimal radial basis function neural network
摘要
Abstract
In order to deal with the problem that the usual flatness pattern recognition methods based on neural network have some flaws which restrict their applications,i, e. ,lower precision for the obtained networks, lower velocity for both on-line recognition and complex network modeling,a kind of flatness pattern recognition based on intelligent optimal radial basis function (RBF) neural network was proposed. In the process of modeling the neural network based on some training data,an improved particle swarm optimization algorithm was proposed to optimize both the number of network nodes and the value of network parameters. Therefore,the approach has simpler structure and better generalization than before. The simulation experiment results showed that the approach was effective and could increase the precision of flatness control.关键词
板形控制/智能优化算法/模式识别/径向基神经网络Key words
flatness control/ intelligent optimal algorithm/ pattern recognition/ radial basis function neural network分类
计算机与自动化引用本文复制引用
解相朋,杨录山..基于智能优化型径向基神经网络的板形模式识别研究[J].郑州轻工业学院学报（自然科学版）,2012,27(3):89-92,4.基金项目
国家自然科学基金项目(60904017,61074073) （60904017,61074073）
