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A Novel Approach for Forecasting Tourist Arrivals Using Web Search Data and Artificial Intelligence

The development of economic activity has been matched by growth in the tourism industry. According to information, the tourism industry is growing and both the number of domestic and international tourists visiting each year is expanding. Because of this quick expansion, there are now critical co...

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Main Authors:	Sagar, Gulati, Mohitkumar Jagdishchandra, Rathod, Guntaj, J, Varsha, Agarwal
Format:	Article
Language:	English English
Published:	INTI International University 2024
Subjects:	GV Recreation Leisure QA75 Electronic computers. Computer science QA76 Computer software
Online Access:	http://eprints.intimal.edu.my/2020/1/jods2024_40.pdf http://eprints.intimal.edu.my/2020/2/562 http://eprints.intimal.edu.my/2020/ http://ipublishing.intimal.edu.my/jods.html
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spelling	my-inti-eprints.20202024-11-08T03:36:17Z http://eprints.intimal.edu.my/2020/ A Novel Approach for Forecasting Tourist Arrivals Using Web Search Data and Artificial Intelligence Sagar, Gulati Mohitkumar Jagdishchandra, Rathod Guntaj, J Varsha, Agarwal GV Recreation Leisure QA75 Electronic computers. Computer science QA76 Computer software The development of economic activity has been matched by growth in the tourism industry. According to information, the tourism industry is growing and both the number of domestic and international tourists visiting each year is expanding. Because of this quick expansion, there are now critical complications with the management of tourism, such as predicting the arrivals for travel, particularly when a lot of people are visiting appealing locations for particular periods. The proposed Artificial Fish Swarm Optimized Dynamic Gated Recurrent Unit (AFSO-DGRU) approach transforms the forecasting of demand for tourism by utilizing intelligence from swarms to improve forecasts and strategically adapting to fluctuating visitor structures. It ensures accurate and dynamic responses even during times of uncertainty when demand is high. The study used Google Trends to collect data from searches on the web and examine trends in tourist’s interest and demand for travel. By combining innovative artificial intelligence (AI) algorithms with realtime online search data, this study presents a novel way to improve the accuracy of visitor arrival predictions. The proposed method performs better than the existing methods to utilize the parameters such as mean absolute deviation called MAE (42.01), mean square error denoted by MSE (3059.85), mean absolute percentage error defined MAPE (1.34), and RMSPE or root mean square percentage error (1.43). This research utilizes web search data and AI to improve the accuracy of forecasting tourist arrivals, offering valuable insights for understanding tourism trends. INTI International University 2024-11 Article PeerReviewed text en cc_by_4 http://eprints.intimal.edu.my/2020/1/jods2024_40.pdf text en cc_by_4 http://eprints.intimal.edu.my/2020/2/562 Sagar, Gulati and Mohitkumar Jagdishchandra, Rathod and Guntaj, J and Varsha, Agarwal (2024) A Novel Approach for Forecasting Tourist Arrivals Using Web Search Data and Artificial Intelligence. Journal of Data Science, 2024 (40). pp. 1-13. ISSN 2805-5160 http://ipublishing.intimal.edu.my/jods.html
institution	INTI International University
building	INTI Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	INTI International University
content_source	INTI Institutional Repository
url_provider	http://eprints.intimal.edu.my
language	English English
topic	GV Recreation Leisure QA75 Electronic computers. Computer science QA76 Computer software
spellingShingle	GV Recreation Leisure QA75 Electronic computers. Computer science QA76 Computer software Sagar, Gulati Mohitkumar Jagdishchandra, Rathod Guntaj, J Varsha, Agarwal A Novel Approach for Forecasting Tourist Arrivals Using Web Search Data and Artificial Intelligence
description	The development of economic activity has been matched by growth in the tourism industry. According to information, the tourism industry is growing and both the number of domestic and international tourists visiting each year is expanding. Because of this quick expansion, there are now critical complications with the management of tourism, such as predicting the arrivals for travel, particularly when a lot of people are visiting appealing locations for particular periods. The proposed Artificial Fish Swarm Optimized Dynamic Gated Recurrent Unit (AFSO-DGRU) approach transforms the forecasting of demand for tourism by utilizing intelligence from swarms to improve forecasts and strategically adapting to fluctuating visitor structures. It ensures accurate and dynamic responses even during times of uncertainty when demand is high. The study used Google Trends to collect data from searches on the web and examine trends in tourist’s interest and demand for travel. By combining innovative artificial intelligence (AI) algorithms with realtime online search data, this study presents a novel way to improve the accuracy of visitor arrival predictions. The proposed method performs better than the existing methods to utilize the parameters such as mean absolute deviation called MAE (42.01), mean square error denoted by MSE (3059.85), mean absolute percentage error defined MAPE (1.34), and RMSPE or root mean square percentage error (1.43). This research utilizes web search data and AI to improve the accuracy of forecasting tourist arrivals, offering valuable insights for understanding tourism trends.
format	Article
author	Sagar, Gulati Mohitkumar Jagdishchandra, Rathod Guntaj, J Varsha, Agarwal
author_facet	Sagar, Gulati Mohitkumar Jagdishchandra, Rathod Guntaj, J Varsha, Agarwal
author_sort	Sagar, Gulati
title	A Novel Approach for Forecasting Tourist Arrivals Using Web Search Data and Artificial Intelligence
title_short	A Novel Approach for Forecasting Tourist Arrivals Using Web Search Data and Artificial Intelligence
title_full	A Novel Approach for Forecasting Tourist Arrivals Using Web Search Data and Artificial Intelligence
title_fullStr	A Novel Approach for Forecasting Tourist Arrivals Using Web Search Data and Artificial Intelligence
title_full_unstemmed	A Novel Approach for Forecasting Tourist Arrivals Using Web Search Data and Artificial Intelligence
title_sort	novel approach for forecasting tourist arrivals using web search data and artificial intelligence
publisher	INTI International University
publishDate	2024
url	http://eprints.intimal.edu.my/2020/1/jods2024_40.pdf http://eprints.intimal.edu.my/2020/2/562 http://eprints.intimal.edu.my/2020/ http://ipublishing.intimal.edu.my/jods.html
_version_	1817849521280909312
score	13.222552

A Novel Approach for Forecasting Tourist Arrivals Using Web Search Data and Artificial Intelligence

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