Table V

The most important and highest-quality articles using ANNs for tourism and passenger demand forecasting

AuthorsPurposeDemand type and periodDeterminantsModeling
Tsai et al. (2009) Predicting short-term railway passenger demandDaily and monthly passenger demandTicket sales dataMultiple temporal units neural network/Parallel ensemble neural network
Celebi et al. (2009) Predicting light rail passenger demandPassenger demand per 15 minHistoric daily passenger dataANN/ARIMA
Chen, Lai, Yeh (2012) Forecasting tourism demand by decomposing data into a finite set of intrinsic mode functionsMonthly tourism demandHistoric tourist arrivals seriesARIMA/Back propagation neural network/Empirical mode decomposition
Chen, Kuo, Chang, Wang (2012) Predicting the air passenger and cargo demandAnnually air passenger and cargo demandPopulation/GDP/GNP/CPI/Economic growth rate/Hotel rateBack-propagation neural network
Cuhadar et al. (2014) Predicting the cruise tourism demandMonthly passenger demandMonthly foreign tourist arrivals by cruiseRadial basis function ANN/Multi-layer perceptron ANN/Generalized regression ANN
Claveria and Torra (2014) Predicting the tourism demandMonthly tourist arrivals from different countriesMonthly data of tourist arrivalsMulti-layer perceptron ANN/Radial basis function ANN/Elman recurrent neural networks
Noersasongko et al. (2016)Forecasting tourist arrivals in IndonesiaMonthly foreign tourist arrivalsHistoric tourist arrivals to three cities in central JavaGenetic algorithm based neural network
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