Research on Dynamic Forecasting of Corporate Planning Investment Based on a Combined Model

With the increasingly complex environment for grid investment in China, accurately predicting corporate planning investment has become essential for managers to make precise investment decisions. This study first selects total electricity consumption, installed capacity, and depreciation rate of fixed asset as 3 key drivers of grid investment through a correlation analysis based on the internal and external environment of the company. Then, regression models and ARIMA (Auto-Regressive Integrated Moving Average) models are employed to forecast grid infrastructure and production & technical reform investment separately. Finally, a combined forecasting model is constructed using the entropy method and Delphi method to assign weights to each individual forecasting model. The weighted results are used to calculate the growth rate of grid infrastructure and production & technical reform investment, representing the expected fixed asset investment growth rate for the company's “15th Five-Year Plan.” This provides an estimate of the total planned investment during this period, offering a reference for decision-making in grid investment management.