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- Title
基于最小二乘法赋权的 ARIMA-LSTM 模型 预测入境旅游人数 ——以上海市为例.
- Authors
康俊锋; 符悦; 方雷; 李咪咪; 谢玉静; 周朝阳
- Abstract
In order to reduce the secondary impact of the COVID-19 on the tourism industry, accurate prediction of the demand of inbound tourism market during the epidemic period can provide a scientific basis for later recovery and development of tourism. Taking Shanghai as the study area, the number of inbound tourists, major source countries, Google search index, confirmed cases of the epidemic and other data were selected to quantitatively analyze the spatial characteristics and the temporal trend of inbound tourism before and after the epidemic, the ARIMA-LSTM combination model weighted by the least square method was used to predict the number of inbound tourists after the epidemic. The results show that: (1) before and after the outbreak of the epidemic, the Asian tourists occupied the core position of the inbound tourism market, and the proportion of traditional inbound tourists and non-traditional inbound tourists is about 9∶ 1; (2) the number of inbound tourists demonstrates a long-term positive correlation and Granger causality with the Google search index, but there is no significant correlation with the confirmed cases of the epidemic; (3) by comparing the model evaluation indicators, it is found that when the R² value of ARIMA-LSTM model is higher than 0.8, the model fits well, and the prediction error is smaller than that of a single model, and the prediction accuracy is higher, which means that the model can be uniformly applied to the recovery prediction of tourist numbers before, during and after the epidemic; (4) the number of inbound tourists from 2021-2024 is predicted, and it shows that the tourism trend during this period presents an obvious U-shaped change. After the comprehensive release of the epidemic in December 2022, the tourism industry began to gradually recover, and it is expected that the number of inbound tourists will return to the preepidemic tourism level by the end of 2024, that is, the recovery period is about one and a half years.
- Subjects
SHANGHAI (China); INBOUND tourism; TOURISM; LEAST squares; TOURISTS
- Publication
Journal of Zhejiang University (Science Edition), 2023, Vol 50, Issue 4, p508
- ISSN
1008-9497
- Publication type
Article
- DOI
10.3785/j.issn.1008-9497.2023.04.014