Prediction Method Based on Time Series

Jie Zheng; Shunping Ouyang; Jian Kang; Youcun Xiao

doi:10.54097/hset.v47i.8160

Authors

Jie Zheng
Shunping Ouyang
Jian Kang
Youcun Xiao

DOI:

https://doi.org/10.54097/hset.v47i.8160

Keywords:

ARIMA model, forecast, slow rise, SPSS system.

Abstract

In order to predict the development trend of a set of time series data in Yunnan Province in 2023, we collected the daily number of confirmed cases in Yunnan Province from 2020 to 2022. Firstly, according to the data analysis of the current situation of prevention and control in Yunnan Province, ARIMA model is used to predict in SPSS system. The final results showed that the number of confirmed cases in Yunnan Province in each month of 2023 showed a slow upward trend, eventually reaching more than 400. It is recommended to pay attention to the publicity of prevention and control in each state and the popularization of medical equipment.

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