Liping Yan1,*, Wei-Chiang Hong2
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1069-1102, 2021, DOI:10.32604/cmes.2021.016499
Abstract The timely and effective investment risk assessment and forecasting are of great significance to ensure the investment safety and sustainable development of wind energy along the Belt and Road. In order to obtain the scientific
and real-time forecasting result, this paper constructs a novel hybrid intelligent model based on improved cloud
model combined with GRA-TOPSIS and MBA-WLSSVM. Firstly, the factors influencing investment risk of wind
energy along the Belt and Road are identified from three dimensions: endogenous risk, exogenous risk and process
risk. Through the fuzzy threshold method, the final input index system is selected. Secondly, the risk evaluation
method… More >
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