| Title |
Research on Intelligent Decision-making Method of Investment Scheme of High-speed Railway Construction Project |
| Authors |
(Xiaochen Duan) ; (Jingjing Hao) ; (Yanliang Niu) |
| DOI |
https://doi.org/10.5573/IEIESPC.2023.12.6.483 |
| Keywords |
Full life cycle; High-speed railway; Investment decision-making; Non-linear methods |
| Abstract |
This paper proposes a particle swarm optimization algorithm, error back propagation neural network, fuzzy inference system, and other non-linear method models with high fitting degree and accuracy to optimize the scientific and accurate decision-making of investment plans for international high-speed railway projects, solve the problems of lag, linearity, and simplicity in the current investment forecasting and decision-making methods, and maximize the economic and social benefits of investment, based on the mining of historical data of the full life cycle cost. These methods were suitable for the randomness, complexity, and non-linearity presented in the full life cycle of international high-speed rail investment. The investment plan decision-making of international high-speed railway construction projects was conducted. The investment error of the selected line construction stage was 1.85%, and the operating investment error from November 14, 2007, to now was 0.64%, which is within the allowable range of ±3%. The ratio of operating investment in the next 80 years to that in the first 20 years was five. The built model was applied to three alternative routes, and the predicted results according to the model were the same as the selected routes in the actual project. |