Affiliation:
1. Guangxi Medical University
Abstract
Abstract
In year 2020, a large-scale outbreak of pneumonia caused by new coronavirus has affected the development of many industries and enterprises in China. Under the strong leadership of the Chinese government, the development of the epidemic situation in China has been well controlled. The development of various industries also began to show a good situation, many large-scale sports competitions also need to be restored. In order to ensure the normal development of large-scale sports events, we need to consider the development of epidemic situation to determine the time of sports events. Based on the study of FPGA theory, this paper designs a specific scheme of programming and system debugging, which includes a variety of program operations. In order to better predict the situation of the epidemic situation, this paper also uses the basic knowledge of machine learning to establish a relevant model to evaluate the situation of large-scale sports events under the development of the epidemic situation, and provide feasible suggestions for the recovery of large-scale sports events under the epidemic situation.
Publisher
Research Square Platform LLC
Reference17 articles.
1. One step-ahead ANFIS time series model for forecasting electricity loads;Cheng CH;Opt Eng,2010
2. Ding, Besanger Y (2011) Time series method for short-term load forecasting using smart metering in distribution systems. In: Proceeding of the IEEE Trondheim PowerTech 58(7) 1–6
3. A living environment prediction model using ensemble machine learning techniques based on quality of life index;Erdoğan Z;J Ambient Intell Human Comput,2019
4. Computational intelligence approaches for energy load forecasting in smart energy management grids: state of the art, future challenges, and research directions;Fallah SN;Energies,2018
5. A survey on ARIMA forecasting using time series model;Farhath ZA;Int J Comput Sci Mobile Comput,2016