现代制造工程Issue(11)：18-24,7.
采用 KPCA-BP 神经网络的并联机构全局综合性能评价方法研究
Research on global comprehensive performance evaluation method of parallel mechanism based on KPCA-BP neural network
摘要
Abstract
Due to the diversity and nonlinear correlation of the parallel mechanism’ s single performance indexes,Kernel Principal Component Analysis ( KPCA) and Back Propagation( BP) neural network technology could be applied to construct KPCA-BP neu-ral network model for comprehensive performance evaluation of parallel mechanism.Through proper sampling,the input data of BP neural network are dealt by KPCA in advance, then the nonlinear relationships among single performance indexes could be re-vealed,and BP neural network could always be simplified to accelerate learning speed and improve forecast accuracy.Further-more,a new global comprehensive performance evaluation method of parallel mechanism is proposed based on various performance indexes,providing scientific basis for optimum order of parallel mechanism’ s working tasks.关键词
并联机构/综合性能评价/全局方法/KPCA方法/BP神经网络/任务优选Key words
parallel mechanism/comprehensive performance evaluation/global method/KPCA method/BP neural network/opti-mum task分类
建筑与水利引用本文复制引用
孙志娟,赵京,戴京涛..采用 KPCA-BP 神经网络的并联机构全局综合性能评价方法研究[J].现代制造工程,2014,(11):18-24,7.基金项目
国家自然科学基金项目（51075005）；北京市科技计划课题项目 （）
