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1 000 MW级火电机组项目的开发前期存在诸多风险,这些风险的防控对投资者至关重要,为此建立了1 000 MW级火电项目前期风险元传递模型,以便为1 000 MW级火电项目前期风险管理者提供决策依据。根据1 000 MW火电项目前期风险元的特点,分析了风险元的分布情况,在此基础上构建了1 000 MW级火电项目前期风险元传递模型,运用蒙特卡洛模拟法确定了火电项目前期风险元发生的概率,探讨了火电项目前期风险元传递的结构,建立了1 000 MW级火电项目前期前馈(back propagation,BP)神经网络型风险元传递算法,并进行了算例仿真,构建了学习样本集,在Matlab 7.0平台上使用样本集对网络进行了训练和测试。测试结果表明,所建立的风险元传递模型具有正确性和可行性,该模型能有效控制项目投资风险。
There are many risks in the pre-development phase of 1 000 MW thermal power plant project, and the prevention and control of these risks are very important to investors. Therefore, a pre-stage risk element transfer model of 1 000 MW thermal power project has been set up to provide a 1 000 MW thermal power project Early stage risk managers provide a basis for decision making. Based on the characteristics of risk elements in the early stage of 1 000 MW thermal power project, the distribution of risk elements is analyzed. Based on this, the early stage risk element transfer model of 1 000 MW thermal power project is constructed and the pre-risk of thermal power project is determined by Monte-Carlo simulation The risk element transmission structure at the early stage of thermal power project is discussed, and the risk element transfer algorithm of back propagation (BP) neural network at the early stage of 1000 MW thermal power project is established. The simulation example is given to construct the Learning sample sets, the network was trained and tested using a sample set on the Matlab 7.0 platform. The test results show that the established model of risk element transfer is correct and feasible, and the model can effectively control the project investment risk.