Hybrid Modeling for Forecasting of Domestic Cultural Tourism Demand in Tehran

In recent years, with the changing pattern of holidays and the formation of short-term holidays, cities have found the opportunity for tourism development. One of the most important types of domestic tourism in Tehran, based on the statistics of the National Center of Statistics and the views of the experts in this area, is cultural tourism. For this purpose, the present study seeks to propose models for forecasting effective variables on forecasting domestic cultural tourism demand in Tehran. To do this, data from years 2002 to 2019 were used and analyzed. Independent variable of this study is the number of domestic business tourists in Tehran, and dependent variables were selected based on Delphi and Fuzzy DEMATEL techniques. The model framework is a combination of regression, fuzzy neural network, and SVR algorithm, which combines these methods to measure forecast errors and compare the methods. The results of this research show that the proposed hybrid approach of regression and Adaptive Neuro-Fuzzy Inference System (ANFIS) can have better prediction than other methods for forecasting domestic Business tourism.