节点文献
基于最小二乘法的产品满意度预测模型
Product Customer Satisfaction Predictive Model Based on LS
【摘要】 在简要分析产品满意度对企业的重要性和国内外相关研究的基础上,通过引入最小二乘算法,建立了一种产品满意度预测模型。通过数据刷新,建立了动态的模型修正机制,以提高模型的预测精度,从而为企业确定何时应该改造其产品提供了重要依据。
【Abstract】 Through analyzing significance of product customer satisfaction and its study status,a kind of product customer satisfaction predictive model was built based on least square algorithm.In order to improve predictive precision of the model,the dynamic model revisable mechanism has been set up by refurbishing the data,so that it offers important basis to enterprises determining when they should reform their products.
【关键词】 产品满意度;
预测模型;
最小二乘;
线性回归;
渐消记忆递推;
【Key words】 product customer satisfaction; predictive model; least square(LS); linear regression; gradual reducing memory recursion;
【Key words】 product customer satisfaction; predictive model; least square(LS); linear regression; gradual reducing memory recursion;
【基金】 浙江省自然科学基金资助项目(502156,M703100);教育部科学技术研究重点项目(205066)
- 【文献出处】 中国机械工程 ,China Mechanical Engineering(中国机械工程) , 编辑部邮箱 ,2005年20期
- 【分类号】F224;
- 【被引频次】17
- 【下载频次】484