Abstract
The CPI index is the final price of social products and services. It is an important indicator for economic analysis and decision-making, monitoring and control of the overall price level, and national economic accounting. Because the CPI index is originally a univariate data indicator, in order to better predict the economic impact of the new coronavirus pneumonia by analyzing the CPI index, in this paper we chose the gray prediction model that has an excellent predictive effect on univariate data. Firstly, we got all CPI data from 2015 to 2019 from the Oriental Wealth Data Center. Secondly we predicted the CPI index for January, February, and March 2020 by using the gray prediction model. Thirdly, the trend of the forecast data was visualized with Python. Finally, the predicting result was compared with the real data, and the reason for the difference was analyzed.
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Acknowledgments
This research was funded by the National Natural Science Foundation of China (No. 61304208), Scientific Research Fund of Hunan Province Education Department (18C0003), Research project on teaching reform in colleges and universities of Hunan Province Education Department (20190147), Changsha City Science and Technology Plan Program (K1501013-11), Hunan Normal University University-Industry Cooperation. This work is implemented at the 2011 Collaborative Innovation Center for Development and Utilization of Finance and Economics Big Data Property, Universities of Hunan Province, Open project, grant number 20181901CRP04.
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Sheng, Y., Zhang, J., Tan, W., Wu, J., Lin, H., Sun, G. (2021). Application of Grey Forecasting Model to CPI Index Forecast. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Advances in Artificial Intelligence and Security. ICAIS 2021. Communications in Computer and Information Science, vol 1423. Springer, Cham. https://doi.org/10.1007/978-3-030-78618-2_25
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DOI: https://doi.org/10.1007/978-3-030-78618-2_25
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