Prediction of Tourism Demand in Iran by Using Artificial Neural Network (ANN) and Supporting Vector Machine (SVR)

Seyedehelham Sadatiseyedmahalleh, Nasim Heidari Bateni, Nazanin Heidari Bateni


This research examines and proves this effectiveness connected with artificial neural networks (ANNs) as an alternative approach to the use of Support Vector Machine (SVR) in the tourism research. This method can be used for the tourism industry to define the turism’s demands in Iran. The outcome reveals the use of ANNs in tourism research might result in better quotations when it comes to prediction bias and accuracy. Even more applications of ANNs in the context of tourism demand evaluation is needed to establish and validate the effects.


Iran; Tourism; Artificial Neural Network (ANN); Support Vector Machine (SVR)

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