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。
An approach bssed 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 resuits 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.
出处
《中国石油大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2006年第1期146-149,156,共5页
Journal of China University of Petroleum(Edition of Natural Science)
基金
山东省自然科学基金资助项目(Y2003H01)
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
oil refining enterprises
performance evaluatioh
entropy technology
technique for order preference by similarity to ideal solution method
artificial neural network
synthetic evaluation
