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一种基于熵权多目标决策和人工神经网络的炼油企业绩效评价方法
引用本文:宋杰鲲,张在旭,张晓慧. 一种基于熵权多目标决策和人工神经网络的炼油企业绩效评价方法[J]. 中国石油大学学报(自然科学版), 2006, 30(1): 146-149,156
作者姓名:宋杰鲲  张在旭  张晓慧
作者单位:中国石油大学,经济管理学院,山东,东营,257061
基金项目:教育部科学技术研究项目
摘    要:提出了一种基于熵权多目标决策的逼近理想解法(TOPSIS)和人工神经网络(ANN)的炼油企业绩效评价方法,以熵权TOPSIS的企业绩效评价结果作为学习样本,对神经网络进行训练、测试,进而对指标加以赋权,最终得到了企业绩效综合评判式,并将其用于炼油企业绩效评价。实例分析结果表明,该方法科学有效、实际可行,具有一定的智能性,为炼油企业绩效评价提供了一种新的途径。

关 键 词:炼油企业  绩效评价  熵技术  多目标决策的逼近理想解法  人工神经网络  综合评价
文章编号:1673-5005(2006)01-0146-04
收稿时间:2005-06-30
修稿时间:2005-06-30

An approach based on entropy-weighted technique for order preference by similarity to ideal solution and artificial neural network for oil refining enterprises performance evaluation
SONG Jie-kun,ZHANG Zai-xu,ZHANG Xiao-hui. An approach based on entropy-weighted technique for order preference by similarity to ideal solution and artificial neural network for oil refining enterprises performance evaluation[J]. Journal of China University of Petroleum (Edition of Natural Sciences), 2006, 30(1): 146-149,156
Authors:SONG Jie-kun  ZHANG Zai-xu  ZHANG Xiao-hui
Affiliation:College of Economic Administration in China University of Petroleum, Dongying 257061, China
Abstract:An approach based on entropy-weighted technique for order preference by similarity to ideal solution(TOPSIS) method and artificial neural network(ANN) was proposed for oil refining enterprises performance evaluation.Using the results of entropy-weighted TOPSIS method as learning sample to train and test the artificial neural network,the weight of performance indicator and a synthetic evaluation formula were obtained.The oil refining enterprises performance evaluation was calculated by the formula.An example testifies the efficiency,practicability and intellectual ability of the method.
Keywords:oil refining enterprises   performance evaluatioh   entropy technology   technique for order preference by similarity to ideal solution method   artificial neural network   synthetic evaluation
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