Evolutionary Computing and Applications in the Tourism Sector for its Sustainable Development - Case Study: Using ANFIS for Forecasting Tourism Demand

摘要

The paper presents a new technique in the field of tourism modelling in order to forecast the tourism demand. Techniques from the Artificial Neural Networks and from fuzzy logic have been combined to generate a neuro-fuzzy model to forecast the tourism demand on next year in island of Crete. The tourist practitioners are very interesting in tourism forecasts in order to plan more effectively tourism strategies. To modeling the complexity and the uncertainty of tourism environment is important to apply fuzzy techniques. The input of the model is a time series of the previous annual overnight stays. Classical statistics measures are calculated in order to asses the model performance. Further the results are compared with an ARMA and an AR model. The results are very encouraged.