Electricity consumption forecasting method based on MPSO-BP neural network model
This is an incremental improvement for electricity consumption forecasting in specific industrial settings.
This paper tackled electricity consumption forecasting by constructing an MPSO-BP neural network model using historical data from a mineral company in China, resulting in improved convergence and accuracy compared to traditional methods like BP and PSO.
This paper deals with the problem of the electricity consumption forecasting method. An MPSO-BP (modified particle swarm optimization-back propagation) neural network model is constructed based on the history data of a mineral company of Anshan in China. The simulation showed that the convergence of the algorithm and forecasting accuracy using the obtained model are better than those of other traditional ones, such as BP, PSO, fuzzy neural network and so on. Then we predict the electricity consumption of each month in 2017 based on the MPSO-BP neural network model.