【摘要】：為提高水電BOT項目投資風險評估水平,針對其投資風險影響因素的非線性、模糊性及不確定性等特點,構建水電BOT項目投資風險識別矩陣,應用徑向基函數(shù)神經(jīng)網(wǎng)絡建立水電BOT項目的投資風險評估RBF模型;運用Matlab建構風險評估模擬程序并預測出項目的投資風險等級,為風險管理提供定量計算方法。算例仿真結果得出該項目的綜合風險評估值為0.581 6,與實際情況相符,表明該模型在評估水電BOT項目投資風險上具有可行性。
[Abstract]:In order to improve the investment risk assessment level of hydropower BOT project, aiming at the nonlinearity, fuzziness and uncertainty of the influencing factors of investment risk, the investment risk identification matrix of hydropower BOT project is constructed. The radial basis function neural network is used to establish the investment risk assessment RBF model of hydropower BOT project. The risk assessment simulation program is constructed by using Matlab and the investment risk grade of the project is forecasted, which provides a quantitative calculation method for risk management. The simulation results show that the comprehensive risk assessment value of the project is 0.581, which is consistent with the actual situation, which indicates that the model is feasible in evaluating the investment risk of hydropower BOT project.
【作者單位】： 三峽大學水利與環(huán)境學院;
【分類號】：TV51

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