Forecasting Inbound Tourism in Uzbekistan: Leveraging AI and ARIMA Models for Economic Growth Insights

Manik Arora,Gurinder Singh,Danish Ather, Naina Chaudhary, Rajneesh Kler

2023 4th International Conference on Computation, Automation and Knowledge Management (ICCAKM)(2023)

引用 0|浏览0
暂无评分
摘要
Foreign tourists serve as one of the strong pillars in economic growth and prosperity for many countries globally. Uzbekistan is no exception, wherein the data suggests that it attracts substantial number of foreign tourists, specially post pandemic. It is observed that there are certain seasons in which the tourist's activity is at its peak. Looking at the data we see the seasonality in the trends. Motivated by this fact the current study tries to forecast the number of inbound tourists into Uzbekistan by utilising ML based modelling. Particularly we use the Auto Regressive Moving Average models to predict. Different models are tested and the best one picked to exhibit the forecast. The findings show the potential of AI and ML for predictive analytics in the tourism industry overall and provide useful information for anyone working in the Uzbek tourism sector. The present study paves the way for further investigation and practical application of cutting-edge methods for data analysis in strategic planning and decision-making.
更多
查看译文
关键词
Artificial Intelligence,Machine Learning,Uzbekistan Tourism,ARIMA Models,Predictive Analytic
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要