Title: New energy industry investment risk assessment method based on fuzzy AHP
Authors: Lianguang Mo
Addresses: School of Management, Hunan City University, Yi yang 413000, China
Abstract: In order to improve the accuracy, efficiency and comprehensiveness of investment risk assessment, a new energy industry investment risk assessment method based on fuzzy AHP is proposed. Firstly, the random forest algorithm is used to predict the investment risk of new energy industry. Secondly, the fuzzy AHP method is used to construct the risk assessment system, the normalisation and consistency test are used to deal with the assessment indicators, and the weight of the assessment indicators is calculated. Finally, based on the evaluation index system, a new energy industry investment risk evaluation model based on multiple regression analysis is established to realise the new energy industry investment risk evaluation. The experimental results show that the highest accuracy of the evaluation results of the proposed method is more than 80%, the evaluation efficiency is high, and the evaluation results are more comprehensive.
Keywords: fuzzy AHP; risk assessment; random forest algorithm; cart algorithm; multiple regression analysis.
DOI: 10.1504/IJGEI.2023.132018
International Journal of Global Energy Issues, 2023 Vol.45 No.4/5, pp.436 - 447
Received: 30 Apr 2022
Accepted: 27 Jul 2022
Published online: 06 Jul 2023 *