基于模糊神经网络的交合分析改进方法

中国管理科学 ›› 2008, Vol. 16 ›› Issue (1): 117-124.

基于模糊神经网络的交合分析改进方法

李春好, 刘成明

吉林大学管理学院吉林长春130025

收稿日期:2007-04-13 修回日期:2007-11-30 出版日期:2008-02-28 发布日期:2008-02-28
作者简介:李春好(1967- ),男(汉族),吉林大学管理学院教授,博士生导师,系主任,博士/出站博士后(日本京都大学),研究方向:复杂系统管理决策.
基金资助:
国家自然科学基金项目(70471015);吉林大学创新基金项目(2004g11)

An Improved Conjoint Analysis Based on FNN

LI Chun-hao, LIU Cheng-ming

School of Management, Jilin University, Changchun 130025, China

Received:2007-04-13 Revised:2007-11-30 Online:2008-02-28 Published:2008-02-28

摘要/Abstract

摘要： 为了克服传统交合分析法(CA)存在的总体效用模型可能会失效及没有较好反映评价问题内在复杂作用关系和没有考虑到专家主观判断不准确性的缺陷,本文借鉴从定性到定量综合集成的复杂系统分析方法论,应用模糊神经网络技术,提出一种基于模糊神经网络的交合分析改进方法。该方法能够比较有效地近似反映出复杂系统蕴含的、难以为专家识别的内在复杂作用机理,因而是一种能够适应各种系统评价问题的一般性、普适性方法。数值验证的结果表明,应用基于模糊神经网络的交合分析改进方法得出的待评价对象排序结果明显好于传统CA法。这说明该方法不但是科学的,而且是比传统CA法更为有效的。

关键词: 交合分析法, 模糊神经网络, 语言型信息, 系统机理

Abstract: Such drawbacks of CA as probably being invalid under some conditions,having not enough ability to well reflect inherent relations of complex systems,and not considering the inaccurate characteristic of evaluations given by valuators,are pointed out. To overcome the three drawbacks,according to the thought of the meta-synthesis from qualitative analysis to quantitative analysis of complex system theory, and based on the theory of the technique of fuzzy neural network,the improved CA based on FNN is presented. The distinguished advantages of the presented approach lie in that it can well capture inherent reladons of complex systems,and thus it is a general approach. The results of numerical demonstration analysis show that the rank of evaluated objects got by the developed approach is much closer to the real,and proves to be more reasonable than the classical CA.

Key words: conjoint analysis, fuzzy neural network, linguistic information, system mechanism

中图分类号:

N94
C931

李春好, 刘成明. 基于模糊神经网络的交合分析改进方法[J]. 中国管理科学, 2008, 16(1): 117-124.

LI Chun-hao, LIU Cheng-ming. An Improved Conjoint Analysis Based on FNN[J]. Chinese Journal of Management Science, 2008, 16(1): 117-124.