Title :
An Enhanced Approach for Investment Risk Forecasting of Electric Power Projects
Author :
Zhang, Cunyan ; Li, Yiming ; Liu, Mengyan ; Liu, Zhibin
Author_Institution :
Sch. of Bus., Agric. Univ. of Hebei, Baoding, China
Abstract :
The electric power projects face the uncertain external environment, they are complex of the projects themselves and the capabilities of the designers, erectors and operator are limited, which make the risk indices of the power projects investment are extremely complicated, including financial risk, technology risk, production risk, market risk, management risk and environmental risk. To evaluate the risk investment projects scientifically and accurately, this paper proposes an enhanced method of adaptive neuro-fuzzy inference system (ANFIS). The ANFIS avoids the fuzziness characteristic of the projects information itself and the circumstances of the neural network cannot express the fuzzy language. The evaluation of 10 electric plant projects shows that the emulation results given by this approach are effective and feasible.
Keywords :
fuzzy reasoning; power system economics; technological forecasting; ANFIS; adaptive neuro-fuzzy inference system; designers; electric power projects; enhanced approach; environmental risk; erectors; financial risk; investment risk forecasting; management risk; market risk; operator; production risk; technology risk; Adaptive systems; Energy management; Environmental management; Financial management; Investments; Power system management; Production; Project management; Risk management; Technology management; ANFIS; electric power project; forecasting; investment risk;
Conference_Titel :
Computer Science and Engineering, 2009. WCSE '09. Second International Workshop on
Conference_Location :
Qingdao
Print_ISBN :
978-0-7695-3881-5
DOI :
10.1109/WCSE.2009.615
