Interpretable tourism demand forecasting with temporal fusion transformers amid COVID-19

Binrong Wu; Lin Wang; Yu‐Rong Zeng

doi:10.1007/s10489-022-04254-0

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Interpretable tourism demand forecasting with temporal fusion transformers amid COVID-19

Binrong Wu Lin Wang Yu‐Rong Zeng

Year: 2022 Journal: Applied Intelligence Vol: 53 (11)Pages: 14493-14514 Publisher: Springer Science+Business Media

DOI: 10.1007/s10489-022-04254-0

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Keywords:

Computer science Tourism Latent Dirichlet allocation Interpretability Convolutional neural network Sentiment analysis Demand forecasting Artificial intelligence Coronavirus disease 2019 (COVID-19) Machine learning Data mining Operations research Topic model Data science Geography

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Diverse Aspects of Tourism Research

Social Sciences → Social Sciences → Sociology and Political Science

Digital Marketing and Social Media

Social Sciences → Social Sciences → Sociology and Political Science

Halal products and consumer behavior

Social Sciences → Social Sciences → Sociology and Political Science

Interpretable tourism demand forecasting with temporal fusion transformers amid COVID-19

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