Prediction of Foreign Tourists Arrival Boosting Indian Coastal Tourism Economy


Avijit Chakraborty
Computer Science and Engineering, Techno Engineering College Banipur, W.B


Background: Marine Coastal Tourism is one of the important aspects of economical growths. Tour operators are facing a huge financial loss due to Covid-19. Tourism is one of the major areas for sustainable economic growth of any country but due to ongoing pandemic, people around the world are suffering a lot in every aspect. Specially in case of travel cancelling flight tickets, hotels as a result tourism are mostly affected [1][2][3], it includes not limited to coastal tourism also.

Objective: This study is to predict the coastal tourist’s flow which will boost economy through foreign exchange [3][4][5].

Methodology: This study is based on secondary data. Monthly wise data of foreign tourist’s arrival of India from 30th April 1989 to 31st March 2020 (369 months) can be collected Centre for Monitoring Indian Economy (economic outlook, 2020). After Collection of data it will move on to processing part. For that data sets are feeding into neural network (LSTM NN) to predict the tourist’s flow.

Results and Discussion: LSTM NN is to predict Tourists flow. The data sets are feeding into as an input of neural network is known as training data set then for output having tested data set for prediction and this LSTM NN uses an appropriate gradient-based learning algorithm.

Conclusion and future work: This finding is having some limitations to predict different forecasting weather conditions that are also important parameter to predict foreign tourist arrival deep learning will be used for getting better results. This contributes to process optimization of the Tourism Industry, driving immense business growth.

January 28, 2022