运筹与管理Issue(6)：88-98,11.
基于DEA和神经网络集成模型的我国基础设施投资有效性预测研究
Combined DEA and Neural Network for Predicting Investment Validityof Infrastructure on China
摘要
Abstract
Combined model of data envelopment analysis( DEA) and neural network for predicting investment validity of infrastructure on China is proposed in this paper. Firstly, investment efficiency on infrastructure based on DEA method from 1993 to 2007 is evaluated to obtain the basic data to predict investment validity. And then, according to the classifying samples which is established based on the evaluated results with DEA method, the scale validity and technical validity of infrastructure is separately predicted with the multi-layer perceptron neural network ( MLP-NN) . The results show that the prediction of investment validity on infrastructure is feasible, and the response rate and the recall have an obvious advantage by comparing with RBF neural network approach and C-SVM method and logistic regression. DEA-MLP-NN method is more effective.关键词
工程管理/预测/数据包络分析/神经网络/基础设施投资Key words
engineering management/ predicting/ DEA/ neural network/ infrastructure investment分类
管理科学引用本文复制引用
李玉龙,李忠富..基于DEA和神经网络集成模型的我国基础设施投资有效性预测研究[J].运筹与管理,2011,(6):88-98,11.基金项目
国家自然科学基金资助项目(G0724003) （G0724003）
中财121人才工程青年博士发展基金资助项目(QBJGL201006) （QBJGL201006）
