Predicting the number of tourists using machine learning
Abstract
This paper provides an overview of current models of machine learning from time series and their application for the purpose of predicting the number of tourist visits in the coming period. The emergence of the Covid-19 virus has generally had a major impact on Tourism and has introduced great uncertainty in this area. The application of machine learning and an attempt to predict the number of tourist visits in the coming period, can be useful to those who deal with the offer in this area.
References
Chollet F. et al., 2015. Keras. [Na mreži]
Available at: https://keras.io
[Poslednji pristup 2021].
Chollet, F., 2018. Deep Learning with Python. s.l.:Manning Publications Co..
Dozat, T., 2016. Incorporating Nesterov Momentum into Adam. s.l., ICLR 2016.
Fotiadis, A., Polyzos, S. & Huan, T.-C. T., 2021. The good, the bad and the ugly on COVID-19 tourism recovery. Annals of tourism research, Tom 87.
Ghalehkhondabi, I., Ardjmand, E., Young, W. A. & Weckman, G. R., 2019. A review of demand forecasting models and methodological developments within tourism and passenger transportation industry. Journal of tourism futures, 5(1), pp. 75-99.
Graves, A., 2013. Generating Sequences With Recurrent Neural Networks. arXiv:1308.0850.
Huber , P. J., 1964. Robust Estimation of a Location Parameter,. The Annals of Mathematical Statistics, 35(1), pp. 73-101.
Republički zavod za statistiku, 2021. Dolasci i noćenja turista po regionima - mesečni podaci. [Na mreži]
Available at: https://data.stat.gov.rs/Home/Result/220203?languageCode=sr-Cyrl
[Poslednji pristup 04 2021].
Sun, S., Wei, Y., Tsui, K.-L. & Wang, S., 2019. Forecasting tourist arrivals with machine learning and internet search index. Tourism Management, Tom 70, pp. 1-10.
TensorFlow, 2015. TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems. [Na mreži]
Available at: http://tensorflow.org/
[Poslednji pristup 2021].
TensorFlow, 2021. Time series forecasting. [Na mreži]
Available at: https://www.tensorflow.org/tutorials/structured_data/time_series
[Poslednji pristup 2021].
Zaborovskaia, O., Sharafanova, E. & Maksanova, L., 2020. Scenario Forecasting Tourist Flows during the COVID-2019 Pandemic. International Journal of Technology, 11(8), pp. 1570-1578.
Zhang, H., Song, H., Wen, L. & Liu, C., 2021. Forecasting tourism recovery amid COVID-19. Annals of Tourism Research, 87(4).