DocumentCode :
3396021
Title :
Research of the risk assessment of thermal power project investment based on Artificial Neural Networks
Author :
Yonggui He ; Chang Liu ; Tianxiang Huang
Author_Institution :
Sch. of Bus. Adm., North China Electr. Power Univ., Baoding, China
fYear :
2011
fDate :
19-22 Aug. 2011
Firstpage :
1710
Lastpage :
1713
Abstract :
This paper according to the investment phase of thermal power projects analyzes the risk factors affecting project investment, on this basis, establishes risk assessment index system of thermal power project investment, and proposes a viable risk assessment model based on BP (Back Propagation) neural network. This model uses BP neural network´s self-learning feature, through amending the weight constantly in the training process, to make the network´s actual output vector be close to the expecting output value gradually. Through simulation of the example by MATLAB neural network tool, the author verifies the reliability of the model, the study of the example shows that this method provides an effective management tool for the risk assessment of thermal power project investment.
Keywords :
backpropagation; investment; mathematics computing; neural nets; power engineering computing; project management; risk management; thermal power stations; MATLAB neural network tool; artificial neural network; back propagation neural network; risk assessment index system; self-learning feature; thermal power project investment; training process; Biological neural networks; Investments; Mathematical model; Risk management; Thermal analysis; Thermal management; BP neural network; model; risk assessment; thermal power projects;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronic Science, Electric Engineering and Computer (MEC), 2011 International Conference on
Conference_Location :
Jilin
Print_ISBN :
978-1-61284-719-1
Type :
conf
DOI :
10.1109/MEC.2011.6025810
Filename :
6025810
Link To Document :
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