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