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基于最小二乘法的产品满意度预测模型
引用本文:华尔天,李国富,毛明杰,高建华,裴仁清,叶飞帆.基于最小二乘法的产品满意度预测模型[J].中国机械工程,2005,16(20):1831-1834.
作者姓名:华尔天  李国富  毛明杰  高建华  裴仁清  叶飞帆
作者单位:1. 上海大学,上海,200072
2. 宁波大学,宁波,315211
3. 浙江工业大学,杭州,310023
4. 浙江理工大学,杭州,310018
基金项目:浙江省自然科学基金,重庆市应用基础研究基金
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.

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
文章编号:1004-132X(2005)20-1831-04
收稿时间:2005-05-18
修稿时间:2005-05-18

Product Customer Satisfaction Predictive Model Based on LS
Hua Ertian,Li Guofu,Mao Mingjie,Gao Jianhua,Pei Renqing,Ye Feifan.Product Customer Satisfaction Predictive Model Based on LS[J].China Mechanical Engineering,2005,16(20):1831-1834.
Authors:Hua Ertian  Li Guofu  Mao Mingjie  Gao Jianhua  Pei Renqing  Ye Feifan
Affiliation:1. Shanghai University,Shanghai,20072; 2. Ningbo University,Ningbo,315211 ; 3. Zhejiang University of Technology, Hangzhou,310023 ; 4. Zhejiang Sci-Tech University,Hangzhou,310018
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.
Keywords:product customer satisfaction  predictive model  least square(LS)  linear regression  gradual reducing memory recursion
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