An Enhanced Approach for Investment Risk Forecasting of Electric Power Projects

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.