DocumentCode :
2074751
Title :
On post-evaluation of power plant construction project based on improved back propagation neural network
Author :
Niu Dongxiao ; Li Xin ; Zhang Kun ; Liu Yimin
Author_Institution :
Sch. of Econ. & Manage., North China Electr. Power Univ., Beijing, China
fYear :
2010
fDate :
29-31 July 2010
Firstpage :
2458
Lastpage :
2461
Abstract :
Construction project post-evaluation is the feedback link of the project decision management, and it can provide a scientific basis for construction projects in the future. This paper established the post-evaluation indicator system of power plant construction project according to its feature. Based on the improved back propagation neural network by using adaptive learning rate and momentum algorithm, combined with Delphi method and success degree method, the post-evaluation model was established. Through the empirical study on 300 MW power plant construction projects, compared with the traditional back propagation neural network model, the result of improved BP neural network model is more accurate and effective.
Keywords :
backpropagation; construction; decision making; neural nets; power plants; project management; 300MW power plant construction projects; Delphi method; adaptive learning rate; back propagation neural network; momentum algorithm; post evaluation; project decision management; success degree method; Adaptation model; Artificial neural networks; Construction industry; Equations; Mathematical model; Power generation; Training; Improved BP Neural Network; Post-evaluation; Power Plant Construction Project;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2010 29th Chinese
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-6263-6
Type :
conf
Filename :
5572187
Link To Document :
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