基于粗糙集理论的模糊神经网络选择合作公司

Cao Jie, C. Fa
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引用次数: 1

摘要

本文首先建立了动态联盟合作企业的评价模型。其次,采用层次分析法确定权重,剔除冗余条件属性,运用粗糙集理论实现决策规则冗余;数据通过冗余只具有需要的条件属性,但具有原创性知识。运用模糊评价的方法对合作伙伴进行决策出租车。通过隐式学习和练习,评估数据成为神经网络的重要数据,通过输出的神经网络草稿值对评估结果进行验证和匹配。论文最后使用MATLAB6.5进行实例验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cooperate Company Selected by Fuzzy Neural Network on Rough Set Theory
Paper firstly builds evaluation model of cooperate company of dynamic alliance. Paper secondly confirms weighted by AHP and wipes off condition attribute of redundancy and carries through decision-making rule redundancy by applying Rough Set Theory. Data only has condition attribute of needs by redundancy, but it has possession knowledge of originality. Paper carries through decision-making taxis of cooperator by applying fuzzy evaluation. And evaluate data becomes import data of Neural networks by concealed learning and exercitation, estimate result is validated and taxis by draft value of Neural networks exported. Paper finally uses MATLAB6.5 validate it by instance.
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