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Supervised by Ministry of Industry and Information Technology of The People's Republic of China Sponsored by Harbin Institute of Technology Editor-in-chief Yu Zhou ISSNISSN 1005-9113 CNCN 23-1378/T

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Related citation:SUN Bai-qing,Dong JinWei.Effective prediction of DEA model by neural network[J].Journal of Harbin Institute Of Technology(New Series),2009,16(5):683-686.DOI:10.11916/j.issn.1005-9113.2009.05.018.
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Effective prediction of DEA model by neural network
Author NameAffiliation
SUN Bai-qing Economics and Management School,Harbin Institute of Technology,Harbin 150001,China 
Dong JinWei Economics and Management School,Harbin Institute of Technology,Harbin 150001,China 
Abstract:
In this paper,a fast neural network model for the forecasting of effective points by DEA model is proposed,which is based on the SPDS training algorithm.The SPDS training algorithm overcomes the drawbacks of slow convergent speed and partially minimum result for BP algorithm.Its training speed is much faster and its forecasting precision is much better than those of BP algorithm.By numeric examples,it is showed that adopting the neural network model in the forecasting of effective points by DEA model is valid.
Key words:  multi-layer neural network  single parameter dynamic searching algorithm  BP algorithm  DEA forecasting
DOI：10.11916/j.issn.1005-9113.2009.05.018
Clc Number:F224
Fund:

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