Electric Power Material Demand Forecasting Based on Machine Learning
Accurate and reasonable demand forecasting of electric power material can lay a solid foundation for material procure-ment and create favorable conditions for enterprises to coordinate resources in advance.Considering historical demand data and project investment and construction progress,a demand forecasting model based on machine learning is proposed.By comprehen-sively reviewing the influencing factors related to material demand from external factors,internal factors and historical data,the time series algorithm is used to process the data,then a demand forecasting model is constructed through the multivariate neural network algorithm.Taking a company's 10 kV power cable as an example for demand forecasting,the results indicate that the mod-el can effectively predict short-term material demand.
material demand forecastingmultivariate neural networkinfluencing factorstime series
NETL
NSTL
万方数据
维普
