中国机械工程2016，Vol.27Issue(20)：2743-2748,6.DOI:10.3969/j.issn.1004-132X.2016.20.009
基于改进BP神经网络的机床基础部件可再制造性评价模型
Evaluation Model for Machine Tool Basic Parts Remanufacturability Based on Optimized BP Neural Network
摘要
Abstract
To utilize sample data to accomplish the remanufacturability evaluation of the machine tool basic parts,and to improve the prediction accuracy of remanufacturability evaluation of the ma-chine tool basic parts,a BP neural network remanufacturability evaluation model optimized by the simulated annealing algorithm and genetic algorithm was proposed.A BP neural network remanufac-turability evaluation prediction model of the machine tool basic parts was built according to the evalua-tion results of typical remanufacturability evaluation model.The BP neural network evaluation model optimized by the simulated annealing algorithm and genetic algorithm has better initial weights and thresholds to increase the convergence rate and avoid the local convergence.Remanufacturability eval-uation of a machine tool basic parts was taken as an example to demonstrate that the remanufactur-ability evaluation model optimized by simulated annealing algorithm and genetic algorithm has higher prediction accuracy.关键词
可再制造性/综合评价/BP神经网络/模拟退火遗传算法Key words
remanufacturability/comprehensive evaluation/BP neural network/simulated annea-ling genetic algorithm分类
信息技术与安全科学引用本文复制引用
潘尚峰,卢超,彭一波..基于改进BP神经网络的机床基础部件可再制造性评价模型[J].中国机械工程,2016,27(20):2743-2748,6.基金项目
国家科技重大专项(2014ZX04014-011) （2014ZX04014-011）
