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A novel approach to model selection in tourism demand modeling
12 references·15 citing·43 second hop
A novel approach to model selection in tourism demand modeling (2014)A novel approach to model selection in to…The Methodological Progress of Tourism Demand Forecasting: A Review of Related Literature (2011)The Methodological Progress o…Combining linear and nonlinear model in forecasting tourism demand (2011)Combining linear and nonlinea…The tourism forecasting competition (2010)The tourism forecasting compe…SVR with hybrid chaotic genetic algorithms for tourism demand forecasting (2010)SVR with hybrid chaotic genet…An Empirical Comparison of Machine Learning Models for Time Series Forecasting (2010)An Empirical Comparison of Ma…Automatic Time Series Forecasting: The forecast Package for R (2008)Automatic Time Series Forecas…Tourism demand modelling and forecasting—A review of recent research (2007)Tourism demand modelling and …Support vector regression with genetic algorithms in forecasting tourism demand (2006)Support vector regression wit…Recent Developments in Econometric Modeling and Forecasting (2005)Recent Developments in Econom…Review of international tourism demand models (1997)Review of international touri…Forecasting, structural time series models and the Kalman filter (1990)Forecasting, structural time …Forecasting principles and practiceForecasting principles and pr…LSTM-Based Deep Learning Models for Long-Term Tourism Demand Forecasting (2022)LSTM-Based Deep Learning Mode…Interpretable tourism demand forecasting with temporal fusion transformers amid COVID-19 (2022)Interpretable tourism demand …Daily tourism demand forecasting: the impact of complex seasonal patterns and holiday effects (2022)Daily tourism demand forecast…Forecasting Tourism Demand With a New Time-Varying Forecast Averaging Approach (2021)Forecasting Tourism Demand Wi…Inbound tourism demand forecasting framework based on fuzzy time series and advanced optimization algorithm (2020)Inbound tourism demand foreca…Forecasting Monthly Tourism Demand Using Enhanced Backpropagation Neural Network (2020)Forecasting Monthly Tourism D…Ex Ante Tourism Forecasting Assessment (2020)Ex Ante Tourism Forecasting A…A novel BEMD-based method for forecasting tourist volume with search engine data (2020)A novel BEMD-based method for…Spatial-temporal forecasting of tourism demand (2019)Spatial-temporal forecasting …Forecasting tourist arrivals: Google Trends meets mixed-frequency data (2019)Forecasting tourist arrivals:…Forecasting hotel room prices in selected GCC cities using deep learning (2019)Forecasting hotel room prices…Particle Swarm Optimization-Based Support Vector Regression for Tourist Arrivals Forecasting (2018)Particle Swarm Optimization-B…ProfARIMA: A profit-driven order identification algorithm for ARIMA models in sales forecasting (2017)ProfARIMA: A profit-driven or…Forecasting Religious Tourism Demand using Artificial Intelligence Case Study: Mashhad City (2016)Forecasting Religious Tourism…Combination forecasts of tourism demand with machine learning models (2015)Combination forecasts of tour…Time Series Analysis: Forecasting and Control (1977)Application of support vector machines in financial time series forecasting (2001)Forecasting stock market movement direction with support vector machine (2004)A meta-analysis of international tourism demand forecasting and implications for practice (2014)A hybrid ANFIS model based on empirical mode decomposition for stock time series forecasting (2016)New developments in tourism and hotel demand modeling and forecasting (2017)Distribution of the Estimators for Autoregressive Time Series with a Unit Root (1979)Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root (1981)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Climate change and international tourism: A simulation study (2005)The role of transport infrastructure in international tourism development: A gravity model approach (2007)Analysis of international tourist arrivals in China: The role of World Heritage Sites (2009)Time Series Analysis, Forecasting and Control. 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References

  • n.d.Forecasting principles and practice4,364 cited
  • 2008Automatic Time Series Forecasting: The forecast Package for R3,538 cited
  • 2007Tourism demand modelling and forecasting—A review of recent research1,419 cited
  • 2010An Empirical Comparison of Machine Learning Models for Time Series Forecasting793 cited
  • 1997Review of international tourism demand models776 cited
  • 2005Recent Developments in Econometric Modeling and Forecasting524 cited
  • 2006Support vector regression with genetic algorithms in forecasting tourism demand378 cited
  • 2010The tourism forecasting competition286 cited
  • 2010SVR with hybrid chaotic genetic algorithms for tourism demand forecasting264 cited
  • 1990Forecasting, structural time series models and the Kalman filter175 cited
  • 2011Combining linear and nonlinear model in forecasting tourism demand163 cited
  • 2011The Methodological Progress of Tourism Demand Forecasting: A Review of Related Literature112 cited

Cited by

  • 2019Spatial-temporal forecasting of tourism demand90 cited
  • 2019Forecasting tourist arrivals: Google Trends meets mixed-frequency data65 cited
  • 2019Forecasting hotel room prices in selected GCC cities using deep learning

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64 cited
  • 2022Interpretable tourism demand forecasting with temporal fusion transformers amid COVID-1947 cited
  • 2015Combination forecasts of tourism demand with machine learning models45 cited
  • 2020Inbound tourism demand forecasting framework based on fuzzy time series and advanced optimization algorithm43 cited
  • 2021Forecasting Tourism Demand With a New Time-Varying Forecast Averaging Approach43 cited
  • 2020A novel BEMD-based method for forecasting tourist volume with search engine data43 cited
  • 2020Ex Ante Tourism Forecasting Assessment43 cited
  • 2022LSTM-Based Deep Learning Models for Long-Term Tourism Demand Forecasting40 cited
  • 2017ProfARIMA: A profit-driven order identification algorithm for ARIMA models in sales forecasting40 cited
  • 2022Daily tourism demand forecasting: the impact of complex seasonal patterns and holiday effects40 cited
  • 2020Forecasting Monthly Tourism Demand Using Enhanced Backpropagation Neural Network37 cited
  • 2018Particle Swarm Optimization-Based Support Vector Regression for Tourist Arrivals Forecasting34 cited
  • 2016Forecasting Religious Tourism Demand using Artificial Intelligence Case Study: Mashhad City6 cited