Data Analytics Methods in Human Resource Demand Forecasting

Human resources are the first resource for enterprise development, and a reasonable human resource structure will increase the effectiveness of an enterprise’s human resource input and output. Based on a deep understanding of forecasting mining technology, this paper discusses the multiple linear regression method and BP neural network algorithm for human resource demand forecasting. Through modeling, statistical index analysis and significance test, the data mining algorithms are analyzed and compared. The regression equation is obtained, and the demand forecast is made on the number of the enterprise personnel, and the feasibility of the multiple regression model is verified. At the same time, the BP neural network algorithm is described in detail, and an example is given to compare the forecasting results of multiple linear regression method and BP neural network algorithm.