基于RBF网络的水电BOT项目投资风险评估

为提高水电BOT项目投资风险评估水平,针对其投资风险影响因素的非线性、模糊性及不确定性等特点,构建水电BOT项目投资风险识别矩阵,应用径向基函数神经网络建立水电BOT项目的投资风险评估RBF模型;运用Matlab建构风险评估模拟程序并预测出项目的投资风险等级,为风险管理提供定量计算方法。算例仿真结果得出该项目的综合风险评估值为0.581 6,与实际情况相符,表明该模型在评估水电BOT项目投资风险上具有可行性。

Hydropower BOT project investment risk evaluation based on RBF network

To improve the accuracy of investment risk assessment of hydropower BOT projects, and in view of the characteristics of influential factors of BOT investment risk such as nonlinear, vagueness and uncertainty, we build a hydropower BOT project investment risk identification matrix.Based on the risk identification result, we apply the radial basis function neural network to create a hydropower BOT project investment risk assessment RBF model, develop a risk assessment simulation program by Matlab and predict the risk level of investment project to provide a quantitative method for risk management.A case analysis shows that the investment risk value of the project is 0.5816, which is consistent with the actual situation, indicating that the model is feasible in investment risk assessment of hydropower BOT projects.