SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Interpretable tourism demand forecasting with temporal fusion transformers amid COVID-19
16 references·1 citing·45 second hopsampled
Interpretable tourism demand forecasting with temporal fusion transformers amid COVID-19 (2022)Interpretable tourism demand forecasting …Forecasting tourism recovery amid COVID-19 (2021)Forecasting tourism recovery …Forecasting tourism demand with multisource big data (2020)Forecasting tourism demand wi…Bayesian BILSTM approach for tourism demand forecasting (2020)Bayesian BILSTM approach for …Tourism demand forecasting: A deep learning approach (2019)Tourism demand forecasting: A…The M4 Competition: 100,000 time series and 61 forecasting methods (2019)The M4 Competition: 100,000 t…A review of research on tourism demand forecasting: Launching the Annals of Tourism Research Curated Collection on tourism demand forecasting (2019)A review of research on touri…Effective tourist volume forecasting supported by PCA and improved BPNN using Baidu index (2018)Effective tourist volume fore…Disentangling consumer recommendations: Explaining and predicting airline recommendations based on online reviews (2018)Disentangling consumer recomm…Forecasting tourism demand with composite search index (2016)Forecasting tourism demand wi…Forecasting Destination Weekly Hotel Occupancy with Big Data (2016)Forecasting Destination Weekl…Forecasting holiday daily tourist flow based on seasonal support vector regression with adaptive genetic algorithm (2014)Forecasting holiday daily tou…Forecasting Chinese tourist volume with search engine data (2014)Forecasting Chinese tourist v…Can Google data improve the forecasting performance of tourist arrivals? Mixed-data sampling approach (2014)Can Google data improve the f…Beyond the hype: Big data concepts, methods, and analytics (2014)Beyond the hype: Big data con…Forecasting private consumption: survey-based indicators vs. Google trends (2011)Forecasting private consumpti…Time series forecasts of international travel demand for Australia (2002)Time series forecasts of inte…Spatiotemporal analysis and forecasting of public attention to China’s five major religions (2025)Spatiotemporal analysis and f…Trends and random walks in macroeconmic time series (1982)Financial time series forecasting using support vector machines (2003)Tourism demand modelling and forecasting—A review of recent research (2007)Tourism forecasting: A review of methodological developments over the last decade (2018)A decomposition-ensemble approach for tourism forecasting (2020)The impact of financial development on carbon emissions: An empirical analysis in China (2011)Predicting the Present with Google Trends (2012)A Big Data Analytics Method for Tourist Behaviour Analysis (2016)Forecasting tourist arrivals with machine learning and internet search index (2018)Comparing Predictive Accuracy (1994)Comparing Predictive Accuracy (1995)In Search of Attention (2011)New developments in tourism and hotel demand modeling and forecasting (2017)Forecasting sales in the supply chain: Consumer analytics in the big data era (2018)Big data: The next frontier for innovation, competition, and productivity (2011)Business Intelligence and Analytics: From Big Data to Big Impact (2012)Data quality management, data usage experience and acquisition intention of big data analytics (2014)Critical analysis of Big Data challenges and analytical methods (2016)Machine learning on big data: Opportunities and challenges (2017)Setting the future of digital and social media marketing research: Perspectives and research propositions (2020)Big data: a revolution that will transform how we live, work, and think (2013)Progress in information technology and tourism management: 30 years on and 20 years after the internet - Revisiting Buhalis & Law's landmark study about eTourism (2018)Time Series Analysis: Forecasting and Control. (1978)Time series analysis forecasting and control (2009)The good, the bad and the ugly on COVID-19 tourism recovery (2020)Time Series Analysis: Forecasting and Control (1977)An Almost Ideal Demand System (1980)Forecasting with artificial neural networks: (1998)Review of tourism forecasting research with internet data (2020)Tourism Demand and the COVID-19 Pandemic: An LSTM Approach (2020)Time Series Analysis Forecasting and Control. (1971)Another look at measures of forecast accuracy (2006)Strictly Proper Scoring Rules, Prediction, and Estimation (2007)Forecast evaluation for data scientists: common pitfalls and best practices (2022)Forecasting: theory and practice (2022)M5 accuracy competition: Results, findings, and conclusions (2022)Testing the equality of prediction mean squared errors (1997)Consumer Confidence and Consumer Spending (2004)Google Econometrics and Unemployment Forecasting (2009)Now-Casting and the Real-Time Data Flow (2013)An Experimental Application of the DELPHI Method to the Use of Experts (1963)Bounds testing approaches to the analysis of level relationships (2001)A review of early COVID-19 research in tourism: Launching the Annals of Tourism Research's Curated Collection on coronavirus and tourism (2021)Would you enjoy virtual travel? The characteristics and causes of virtual tourists’ sentiment under the influence of the COVID-19 pandemic (2021)Two years of COVID-19 and tourism: what we learned, and what we should have learned (2022)
this work references cited by second hop· second hop is a sample of the most-cited connections

References

  • 2014Beyond the hype: Big data concepts, methods, and analytics4,222 cited
  • 2019The M4 Competition: 100,000 time series and 61 forecasting methods990 cited
  • 2011Forecasting private consumption: survey-based indicators vs. Google trends560 cited
  • 2019A review of research on tourism demand forecasting: Launching the Annals of Tourism Research Curated Collection on tourism demand forecasting526 cited
  • 2019Tourism demand forecasting: A deep learning approach451 cited
  • 2014Forecasting Chinese tourist volume with search engine data432 cited
  • 2021Forecasting tourism recovery amid COVID-19404 cited
  • 2016Forecasting tourism demand with composite search index369 cited
  • 2014Can Google data improve the forecasting performance of tourist arrivals? Mixed-data sampling approach331 cited
  • 2014Forecasting holiday daily tourist flow based on seasonal support vector regression with adaptive genetic algorithm293 cited
  • 2002Time series forecasts of international travel demand for Australia279 cited
  • 2020Forecasting tourism demand with multisource big data260 cited
  • 2018Effective tourist volume forecasting supported by PCA and improved BPNN using Baidu index248 cited
  • 2020Bayesian BILSTM approach for tourism demand forecasting235 cited

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

2016
Forecasting Destination Weekly Hotel Occupancy with Big Data
229 cited
  • 2018Disentangling consumer recommendations: Explaining and predicting airline recommendations based on online reviews200 cited
  • Cited by

    • 2025Spatiotemporal analysis and forecasting of public attention to China’s five major religions3 cited