Risk Assessment of Waste Incineration Power Generation Project Based on BP Neural Network

The waste incineration power generation method can reduce the amount of waste and make it harmless, and can convert it into part of the electric energy. Due to the large amount of project investment and high professional and technical requirements, the cooperation model between the government and social capital is promoted, and social capital is encouraged to participate in infrastructure construction. There are still many risks in the investment, construction, operation stage and exit mechanism of waste incineration power generation projects. BP (Back Propagation) neural network is one of the most widely used training algorithms in artificial neural network algorithms, and has been widely used in prediction, recognition, diagnosis and other fields. We identify the potential risks of waste incineration power generation projects, deal with the risks that have appeared in the process of waste incineration power generation projects, reduce risk losses, and timely curb the expansion of risks are the main tasks of risk management of waste incineration power generation projects. This paper deeply studies the BP neural network algorithm, comprehensively analyzes various uncertain factors in the development of waste incineration power generation projects, builds a scientific and feasible risk assessment model for waste incineration power generation projects, selects relevant data for simulation analysis, and verifies the effectiveness of the training model.