Tourism Growth Prediction Based on Deep Learning Approach

The conventional tourism demand prediction models are currently facing several challenges due to the excess number of search intensity indices that used as indicators demand. In this work, framework for deep learning-based monthly volumes Macau tourist arrivals was presented. main objective in study is predict growth via one learning algorithms extracting new features. outcome showed performance adopted better than artificial neural network and support vector regression models. Practitioners can rely on identified relevant features from developed understand nature relationships between predictive factors actual volume arrival.