基于粒子群算法的BP神经网络电价预测系统设计

Design of BP Neural Network Electricity Price Forecasting System Based on Particle Swarm Optimization Algorithm

阐述粒子群算法对于BP神经网络初始权值、阈值进行精准计算,提升电力系统的电价可测性。仿真结果表明,神经网络预测模型系统设计对于电价预测有很好的应用效果。

The particle swarm optimization algorithm is described to accurately calculate the initial weight and threshold of BP neural network, so as to improve the electricity price testability of power system. The simulation results show that the design of neural network forecasting model system has a good application effect for electricity price forecasting.