The Use of Artificial Intelligence Models in Predicting the International Demand for Tourism in Syria

Abstract

Many artificial intelligence models have been used in studying and analyzing time series and forecasting their future changes, which focused on forecasting demand in the services sector in general and some of them were linked to forecasting demand for tourism services in particular. References indicated the availability of a high degree of credibility and accuracy in forecasting demand using artificial intelligence models, including the LSTM model. the current study has multiple objectives, including: identifying the LSTM model’s efficiency and ability degree in predict the international demand for tourism in Syria, in addition to determining the accuracy and credibility level in the case of using the LSTM model. Furthermore, the descriptive analytical method was used and the data of the Ministry of Tourism was applied. However, the most important finding is that the LSTM model is highly accurate and credible, wherein the predicted values are very close to the actual values in the three years assigned to the model credibility testing. Additionally, the LSTM model is efficient in predicting the international demand for tourism. Moreover, the use of the LSTM model in prediction makes it highly credible. Finally, the predicted future values of demand for international tourism in Syria indicate a significant increase in demand for international tourism in the predicted years. Based on the results and conclusions, the following can be recommended: Increasing interest in artificial intelligence techniques and using them in the process of analyzing tourism data and predicting future tourism demand in its various forms based on these diverse models. Using more than one model to compare between them, as some of them are suitable for long or short time frames or both.