协同创新环境下的客户知识共享绩效预测模型  

Prediction Model of Customer Knowledge-Sharing Performance in Collaborative Product Innovation Process

作　　者：李晓利[1] 杨育[1] 张晓冬[1] 王小磊[1,2] 曾强[1] 

机构地区：[1]重庆大学机械传动国家重点实验室,重庆400030 [2]华北电力大学机械工程系,河北保定071003

出　　处：《科技进步与对策》2010年第12期112-115,共4页Science & Technology Progress and Policy

基　　金：国家自然科学基金项目(70601037);教育部"新世纪优秀人才支持计划"项目(NCE-07-0908)

摘　　要：为科学地预测协同产品创新过程中客户的知识共享绩效,提出了基于减聚类-模糊神经网络的客户知识共享绩效预测模型,构建了协同创新环境下的客户知识共享绩效评价指标体系;运用模糊减聚类法对网络规则进行了处理,减少了神经网络规则的数目,以免参数膨胀导致网络难以训练。最后,通过算例验证了该模型的可行性和有效性。To predict the customer knowledge-sharing performance in the process of customer collaborative product innovation,based on subtractive clustering and Fuzzy Neural Network,an customer knowledge-Sharing Performance prediction model was proposed in this paper.Firstly,the index system of performance evaluation was constructed.Secondly,fuzzy subtractive clustering was utilized to simplify the rules and reduce the parameters of fuzzy neural network.Furthermore,particle swarm optimization algorithm and genetic algorithm were used to decide the parameters＇ values of fuzzy neural network.Based on the model,the synthetic evaluation values of individuals were got.Finally,an example was given to validate the feasibility and effectiveness of the model.

关 键 词：客户知识 协同产品创新 共享绩效 模糊神经网络 减聚类 

分 类 号：G302[文化科学]