The invention discloses a distribution network material demand multiple regression prediction technology based on
correlation factor analysis. Under the background of rapid development of economy and continuous acceleration of
urbanization pace, an
electric power distribution network project serves as a core part of infrastructure construction, and the importance of demand prediction of the
electric power distribution network project is increasingly prominent. The demand of power distribution network materials is influenced by various factors, such as economic growth,
population change, industrial structure, technical progress and the like, and the related historical data accumulation sample size is small. If only the historical
time sequence data of the material quantity is predicted, on one hand, the prediction effect is limited by the existing
small data sample size, and on the other hand, the prediction result is not accurate enough due to neglecting the influence of other important influence factors. According to the method, four
related factors of the distribution network are comprehensively considered based on
correlation analysis, the four
related factors comprise the number of projects, the issued plan amount, the power supply amount and the GDP, all the influence factors are combined, and the distribution network materials are predicted through multiple regression. According to the invention, auxiliary support can be carried out on material
purchasing related work of a material department, the
purchasing cost and the
inventory cost are saved to a great extent, and the enterprise competitiveness is improved.