Prediction of Information Talent Demand Based on the Grayscale Prediction Model and the BP Neural Network

Abstract

With the increasing popularity of the Internet technology, people are now increasingly accustomed to obtaining information or help through the Internet. Meanwhile, the great development of the information service industry has led to the explosive growth of the demand for information service talents. In recent years, many information service talent demand reports have been released in China, and it has an important guiding significance for information service industry planning. However, there are three problems with the information service industry talent demand reports at present. First, the relevance and support of talent demand analysis and forecast to information service industry planning need to be clarified. Second, the coordination and cooperation of information service personnel demand report preparation need to be improved. The third is the wider application of scientific and reasonable information service personnel demand forecasting models. In the future, we need to develop and use more reasonable information service personnel demand forecasting models and improve the quality of information service personnel demand reports. At the same time, the supporting role of the information service industry in scientific planning needs to be strengthened continuously. Therefore, information service industry talent demand forecasting is of great significance. In this paper, a prediction model of information service talent demand is established by using gray system theory. For the deviations of the GM (1, 1) model, a combined GM (1, 1)-BP neural network prediction model is proposed. The simulation results show that the prediction results of the prediction model in this paper are satisfactory. Therefore, the GM (1, 1)-BP model proposed in this paper can be used as a reference for government decision-making and information service personnel training.