• RAHUL KUMAR
• PREETI SHARMA

Tourists’ get attracted towards Thailand because of its diverse culture and geography. Apart from heritage and culture, the tourists from all over the world come here for various other purposes like medical, business, education and sports. The tourism industry of Thailand is economically important and is growing rapidly. The tourism industry in Thailand helps in the growth of other sectors like agriculture, small scale industries, self-employment, etc. This makes forecasting of tourists’ arrivals in Thailand a prime focus of the government. Forecasting is the process of making predictions of the future based on past and present data and analysis of trends. Tourism forecasting plays an important role in providing awareness and support for future development of the Thailand tourism industry. In this paper, an attempt has been made to forecast tourists’ arrival using ARIMA, Holtwinter and Naïve Bayes Methods.

Forecasting; Holt-Winter’s exponential smoothing model; ARIMA; Auto regression; Moving average; Naïve Bayes

"TIME SERIES FORECASTING FOR THAI TOURISM DATASET", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 9, page no.197-203, September-2022, Available :http://www.jetir.org/papers/JETIRFS06034.pdf

"TIME SERIES FORECASTING FOR THAI TOURISM DATASET", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 9, page no. pp197-203, September-2022, Available at : http://www.jetir.org/papers/JETIRFS06034.pdf