DocumentCode :
3457641
Title :
The Application of Power Plant Construction Investment Estimation Based on Improved Neural Network by PSO
Author :
Zheng-yuan Jia ; Li Tian ; Qingchao Liu
Author_Institution :
Sch. of Bus. Adm., North China Electr. Power Univ., Baoding
fYear :
2008
fDate :
12-14 Oct. 2008
Firstpage :
1
Lastpage :
4
Abstract :
Using BP neural network estimate the investment of the power plant construction project is this paper´s innovative points. First we give the engineering characteristic factors of power plant construction project, then give the value of each qualitative index. Then use improved BP neural network by PSO to estimate the investment. From the result, we can see that is more accuracy and speedily than BP neural network algorithm. Lastly, we can get a satisfaction result. This can be guiding the project construction investment.
Keywords :
backpropagation; civil engineering computing; construction; investment; neural nets; power plants; BP neural network; improved neural network; power plant construction investment estimation; power plant construction project; Cost function; Extrapolation; Feedforward neural networks; Fuzzy neural networks; Investments; Neural networks; Neurons; Power engineering and energy; Power generation; Project management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wireless Communications, Networking and Mobile Computing, 2008. WiCOM '08. 4th International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4244-2107-7
Electronic_ISBN :
978-1-4244-2108-4
Type :
conf
DOI :
10.1109/WiCom.2008.1756
Filename :
4679945
Link To Document :
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