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Oil Refining Enterprise Performance Evaluation Based on DEA and SVM

机译:基于DEA和SVM的炼油企业绩效评价。

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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.
机译:企业绩效评估是企业管理的重要手段,可以诊断企业的整体发展状况。数据包络分析(DEA)是最常用的评估方法之一,而支持向量机(SVM)是一种新的数据挖掘方法,可用于预测和回归。基于DEA和SVM,提出了一种评估和预测企业绩效的方法。首先,采用DEA方法对所有炼油企业的DEA效率进行评估。然后,选择一些决策单元(DMU)的输入/输出数据和结果作为学习实例,以训练SVM网络,而其他实例作为测试示例,以测试网络。如果SVM网络得到充分验证,则可以给出综合评估公式来预测新DMU的DEA效率。一个真实的例子证明了这种方法的效率,实用性和智能性。

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