【摘要】：為提高水電BOT項(xiàng)目投資風(fēng)險(xiǎn)評(píng)估水平,針對(duì)其投資風(fēng)險(xiǎn)影響因素的非線性、模糊性及不確定性等特點(diǎn),構(gòu)建水電BOT項(xiàng)目投資風(fēng)險(xiǎn)識(shí)別矩陣,應(yīng)用徑向基函數(shù)神經(jīng)網(wǎng)絡(luò)建立水電BOT項(xiàng)目的投資風(fēng)險(xiǎn)評(píng)估RBF模型;運(yùn)用Matlab建構(gòu)風(fēng)險(xiǎn)評(píng)估模擬程序并預(yù)測(cè)出項(xiàng)目的投資風(fēng)險(xiǎn)等級(jí),為風(fēng)險(xiǎn)管理提供定量計(jì)算方法。算例仿真結(jié)果得出該項(xiàng)目的綜合風(fēng)險(xiǎn)評(píng)估值為0.581 6,與實(shí)際情況相符,表明該模型在評(píng)估水電BOT項(xiàng)目投資風(fēng)險(xiǎn)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(xué)水利與環(huán)境學(xué)院;
【分類(lèi)號(hào)】：TV51

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本文編號(hào)：2314184