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