SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Tourism Demand Forecasting with Neural Network Models: Different Ways of Treating Information
16 references·12 citing·39 second hop
Tourism Demand Forecasting with Neural Network Models: Different Ways of Treating Information (2014)Tourism Demand Forecasting with Neural Ne…Forecasting tourism demand to Catalonia: Neural networks vs. time series models (2013)Forecasting tourism demand to…Combining linear and nonlinear model in forecasting tourism demand (2011)Combining linear and nonlinea…SVR with hybrid chaotic genetic algorithms for tourism demand forecasting (2010)SVR with hybrid chaotic genet…Support vector regression with genetic algorithms in forecasting tourism demand (2006)Support vector regression wit…Neural Network Forecasting of Tourism Demand (2005)Neural Network Forecasting of…Linear models, smooth transition autoregression, and neural networks for forecasting macroeconomic time series: A re-examination (2005)Linear models, smooth transit…Designing an artificial neural network for forecasting tourism time series (2005)Designing an artificial neura…A comparison of three different approaches to tourist arrival forecasting (2003)A comparison of three differe…Tourism as a long-run economic growth factor: the Spanish case (2002)Tourism as a long-run economi…A practitioners guide to time-series methods for tourism demand forecasting — a case study of Durban, South Africa (2001)A practitioners guide to time…Back-propagation learning in improving the accuracy of neural network-based tourism demand forecasting (2000)Back-propagation learning in …A neural network model to forecast Japanese demand for travel to Hong Kong (1999)A neural network model to for…Forecasting with artificial neural networks: (1998)Forecasting with artificial n…Time series prediction: Forecasting the future and understanding the past (1994)Time series prediction: Forec…Time series forecasting using neural networks (1994)Time series forecasting using…Time series forecasting using neural networks vs. Box- Jenkins methodology (1991)Time series forecasting using…Tourism demand forecasting with spatiotemporal features (2022)Tourism demand forecasting wi…Demand forecasting based machine learning algorithms on customer information: an applied approach (2022)Demand forecasting based mach…Using machine learning and big data for efficient forecasting of hotel booking cancellations (2020)Using machine learning and bi…Revenue management forecasting: The resiliency of advanced booking methods given dynamic booking windows (2020)Revenue management forecastin…Hierarchical pattern recognition for tourism demand forecasting (2020)Hierarchical pattern recognit…Forecasting Tourism Demand with an Improved Mixed Data Sampling Model (2020)Forecasting Tourism Demand wi…Data source combination for tourism demand forecasting (2019)Data source combination for t…A review of demand forecasting models and methodological developments within tourism and passenger transportation industry (2019)A review of demand forecastin…Stacked autoencoder with echo-state regression for tourism demand forecasting using search query data (2018)Stacked autoencoder with echo…Forecasting turning points in tourism growth (2018)Forecasting turning points in…New developments in tourism and hotel demand modeling and forecasting (2017)New developments in tourism a…Using a Single Dendritic Neuron to Forecast Tourist Arrivals to Japan (2016)Using a Single Dendritic Neur…The accuracy of extrapolation (time series) methods: Results of a forecasting competition (1982)Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm (2008)A novel hybridization of artificial neural networks and ARIMA models for time series forecasting (2010)A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition (2012)Time Series Analysis: Forecasting and Control (1977)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Financial time series forecasting using support vector machines (2003)Time series forecasting using a hybrid ARIMA and neural network model (2003)DeepAR: Probabilistic forecasting with autoregressive recurrent networks (2019)Forecasting tourism demand: A review of empirical research (1995)Earthquake devastation and recovery in tourism: the Taiwan case (2002)Effects of user-provided photos on hotel review helpfulness: An analytical approach with deep leaning (2017)Time Series Analysis: Forecasting and Control. (1978)Analysis of international tourist arrivals in China: The role of World Heritage Sites (2009)Time series analysis forecasting and control (2009)Forecasting holiday daily tourist flow based on seasonal support vector regression with adaptive genetic algorithm (2014)Application of support vector machines in financial time series forecasting (2001)Modeling and forecasting tourism demand for arrivals with stochastic nonstationary seasonality and intervention (2002)A meta-analysis of international tourism demand forecasting and implications for practice (2014)Designing a neural network for forecasting financial and economic time series (1996)Improving artificial neural networks’ performance in seasonal time series forecasting (2008)INFORMATION TECHNOLOGY APPLICATIONS IN HOSPITALITY AND TOURISM: A REVIEW OF PUBLICATIONS FROM 2005 TO 2007 (2009)Big data analytics for knowledge generation in tourism destinations – A case from Sweden (2014)Investigating Causal Relations by Econometric Models and Cross-spectral Methods (1969)Distribution of the Estimators for Autoregressive Time Series with a Unit Root (1979)Co-Integration and Error Correction: Representation, Estimation, and Testing (1987)The contribution of tourism development to economic growth in the Korean economy (2003)Tourism as a Long-Run Economic Growth Factor: An Empirical Investigation for Greece Using Causality Analysis (2004)Tourism development and economic growth: A closer look at panels (2007)Combining forecasts: A review and annotated bibliography (1989)Combining forecasts: A review and annotated bibliography (1990)Tourism demand modelling and forecasting—A review of recent research (2007)Where Can Tourism-Led Growth and Economy-Driven Tourism Growth Occur? (2018)Tourism productivity and economic growth (2019)Artificial intelligence for hospitality big data analytics: developing a prediction model of restaurant review helpfulness for customer decision-making (2021)Decision support and expert systems (1993)Neural network techniques for financial performance prediction: integrating fundamental and technical analysis (2003)Using the R-MAPE index as a resistant measure of forecast accuracy (2013)
this work references cited by second hop

References

  • 1998Forecasting with artificial neural networks:4,225 cited
  • 2002Tourism as a long-run economic growth factor: the Spanish case1,587 cited
  • 1994Time series prediction: Forecasting the future and understanding the past841 cited
  • 1991Time series forecasting using neural networks vs. Box- Jenkins methodology407 cited
  • 2006Support vector regression with genetic algorithms in forecasting tourism demand378 cited
  • 2000Back-propagation learning in improving the accuracy of neural network-based tourism demand forecasting344 cited
  • 2003A comparison of three different approaches to tourist arrival forecasting322 cited
  • 1999A neural network model to forecast Japanese demand for travel to Hong Kong309 cited
  • 2005Designing an artificial neural network for forecasting tourism time series286 cited
  • 2005Linear models, smooth transition autoregression, and neural networks for forecasting macroeconomic time series: A re-examination275 cited
  • 2013Forecasting tourism demand to Catalonia: Neural networks vs. time series models270 cited
  • 2010SVR with hybrid chaotic genetic algorithms for tourism demand forecasting264 cited
  • 2001A practitioners guide to time-series methods for tourism demand forecasting — a case study of Durban, South Africa250 cited
  • 1994Time series forecasting using neural networks

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

178 cited
  • 2011Combining linear and nonlinear model in forecasting tourism demand163 cited
  • 2005Neural Network Forecasting of Tourism Demand159 cited
  • Cited by

    • 2017New developments in tourism and hotel demand modeling and forecasting313 cited
    • 2020Using machine learning and big data for efficient forecasting of hotel booking cancellations114 cited
    • 2020Hierarchical pattern recognition for tourism demand forecasting86 cited
    • 2020Forecasting Tourism Demand with an Improved Mixed Data Sampling Model82 cited
    • 2019A review of demand forecasting models and methodological developments within tourism and passenger transportation industry74 cited
    • 2022Demand forecasting based machine learning algorithms on customer information: an applied approach73 cited
    • 2022Tourism demand forecasting with spatiotemporal features69 cited
    • 2018Stacked autoencoder with echo-state regression for tourism demand forecasting using search query data67 cited
    • 2019Data source combination for tourism demand forecasting63 cited
    • 2016Using a Single Dendritic Neuron to Forecast Tourist Arrivals to Japan61 cited
    • 2018Forecasting turning points in tourism growth61 cited
    • 2020Revenue management forecasting: The resiliency of advanced booking methods given dynamic booking windows42 cited