Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (3): 273-278.DOI: 10.3778/j.issn.1002-8331.1910-0364

Previous Articles    

Research on Efficiency Confidence Interval Prediction Model Based on DEA-BP Neural Network

ZHENG Jianfeng, WANG Yingming   

  1. School of Economics and Management, Fuzhou University, Fuzhou 350108, China
  • Online:2021-02-01 Published:2021-01-29



  1. 福州大学 经济与管理学院,福州 350108


In recent years, efficiency prediction is a hot topic of research. However, with the complexity and uncertainty of the evaluation system, the point prediction performance of efficiency will gradually decrease. Based on this, a DEA-BP neural network confidence interval prediction model is proposed. Firstly, the non-archimedes infinite CCR model is constructed to evaluate the efficiency of the system. Secondly, the confidence interval prediction model of BPNN is constructed, and the point prediction is transformed into interval prediction. Finally, the interval comprehensive verification is carried out by PICP, NMPIL and CLC models. The three-stage model is applied to the tourism efficiency forecast of provinces and cities along the “Belt and Road”, and the efficiency of each province and city is classified according to the forecast results and suggestions for improvement are proposed. Because the BPNN confidence interval prediction model is difficult to confirm the best model, the results of this paper still need to be improved, but it has certain reference.

Key words: efficiency prediction, efficiency evaluation, BP neural network, interval prediction



关键词: 效率预测, 效率评价, BP神经网络, 区间预测