Research on the Optimization Method of Electric Power Construction Schedule Based on Neural Network

With the rapid development of the economy and technology, the demand for electricity is rising, so the construction of electricity is increasing year by year. Therefore, the importance of power construction progress management in power construction is also increasing. In order to effectively improve the construction progress in power construction, a power construction progress optimization method based on the BP neural network is proposed. Based on three-dimensional model simulation, the accuracy of construction progress estimation is improved by comparing the simulation progress with the actual construction progress. Firstly, a genetic algorithm is used to establish a 3D model to simulate the progress of the electric power construction site, and the obtained model is bound to the actual construction tasks. Secondly, the electric power construction progress library is established, and the weight of progress evaluation indexes is adjusted. Then, the neural network is used to evaluate the progress of power construction so as to provide early warning for the existence of progress risk. Finally, the proposed optimization method is applied to a specific construction site by using a case study method. The results show that using this method, the success rate of early warning of construction progress is 99.68%.