Oil Refining Enterprise Performance Evaluation Based on DEA and SVM

被引:5
作者
Song, Jiekun [1 ]
Zhang, Zaixu [1 ]
机构
[1] China Univ Petr E China, Coll Econ & Management, Dongying, Peoples R China
来源
WKDD: 2009 SECOND INTERNATIONAL WORKSHOP ON KNOWLEDGE DISCOVERY AND DATA MINING, PROCEEDINGS | 2009年
关键词
refining enterprise; performance evaluation; data envelopment analysis; support vector machine; prediction;
D O I
10.1109/WKDD.2009.43
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Enterprise performance evaluation is an important means of enterprise management, which can diagnose the whole development status of enterprise. Data envelopment analysis (DEA) is one of the most frequently used evaluation methods and support vector machine (SVM) is a novel method of data mining, which can be used for prediction and regression. Based on DEA and SVM, the paper proposes a method for evaluating and predicting enterprise performance. First, DEA method is used to evaluate DEA efficiency of all the oil refining enterprises performance. Then the input/output data and results of some decision making units (DMUs) are selected as the learning examples to train the SVM network and the others are used as the test examples to test the network. If the SVM network is testified well, a synthetic evaluation formula can be given to predict the DEA efficiency of a new DMU. A real example testifies the efficiency, practicability and intellectual ability of this method.
引用
收藏
页码:401 / 404
页数:4
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