Design and Implementation for Innovative Tourism Expert System based on Artificial Intelligence

The tourism sector has long been looked at as a vital engine of economic expansion. The most recent developments in the tourism sector have benefitted governments, international organizations, common people and academia. For developing the tourism sector, it is important to analyze and understand tourist visitor patterns. Tourist forecasting helps maximize the tourism-based economy. The international tourist movement has grown at an unprecedented rate in recent decades, and many countries are concentrating on the tourism economy. While tourists visit a tourist place, spend a significant amount of money on their enjoyment, company, and hotel accommodations. ML algorithms are making significant contributions to forecasting system, and several researchers are working to improve the model’s accuracy. This research has proposed a machine learning approach for forecasting worldwide tourist arrivals that analyses prior quantitative information about visitors so that the governing body can arrange the necessary facilities for visitors accordingly. The proposed model is applied to a dataset compiled over a decade from all countries around the world. The detailed proposed approach and the various results of experiments are explained in this paper.