基于粒子群的产品变型设计时间预测研究  

Predicting Product Variant Design Time Based on PSO Algorithm

作　　者：王兆华[1] 同淑荣[1] 黄丽[2] 

机构地区：[1]西北工业大学管理学院,陕西西安710072 [2]江苏大学电气信息工程学院,江苏镇江212013

出　　处：《计算机与现代化》2015年第9期100-104,共5页Computer and Modernization

基　　金：国家自然科学基金资助项目(70771091);江苏省高校自然科学基金资助项目(12KJB210001)

摘　　要：针对产品变型设计时间难以在产品二次开发前精确预估问题,提出基于粒子群算法与模糊神经网络相融合的时间预测方法。首先,确定时间因素集并给出相应的模糊神经网络(FNN)时间预测算法;其次,采用带极值扰动粒子群(t PSO)优化FNN网络,以解决FNN时间预测算法易陷入局部极值,进化后期收敛速度慢以及全局搜索能力弱等缺陷;最后,以打印机变型设计为例进行分析,结果表明该预测方法可行、有效,能实现产品变型设计时间预估。Before product secondary development, it is very difficult to forecast product variant design time. A variant design time prediction method based on the combination of the extremum disturbed particle swarm optimization （ tPSO） with fuzzy neural net-work （ FNN） is proposed. First of all, the time factor set is designated and the corresponding FNN time prediction model is estab-lished. However, the typical algorithm of FNN is easy to fall into local minimum, slow convergence speed and low learning effi-ciency. And then, the FNN model is optimized by tPSO to overcome disadvantages above. At last, the method is verified by the time prediction of printer variant design. The result indicates that the model is feasible and effective.

关 键 词：产品变型设计 设计时间预测 粒子群算法 模糊神经网络 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]