Multilayer feedforward networks are universal approximators
Neural Networks
Approximation capabilities of multilayer feedforward networks
Neural Networks
Neural network models for time series forecasts
Management Science
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
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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.