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Forecasting hotel room prices in selected GCC cities using deep learning · Study

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ArticleForecasting hotel room prices in selected GCC cities using deep learning

Mohammed Al Shehhi2019

Article2019

Forecasting hotel room prices in selected GCC cities using deep learning

Mohammed Al Shehhi · Andreas Karathanasopoulos

64 citations·0/0 files stored·Journal of Hospitality and Tourism Management

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Forecasting Techniques and Applications Diverse Aspects of Tourism Research Stock Market Forecasting Methods

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References

2019Tourism demand forecasting: A deep learning approach 2014Forecasting Chinese tourist volume with search engine data 2018Forecasting tourist arrivals with machine learning and internet search index 2006Support vector regression with genetic algorithms in forecasting tourism demand 2016Forecasting tourism demand with composite search index 2000Back-propagation learning in improving the accuracy of neural network-based tourism demand forecasting 2003A comparison of three different approaches to tourist arrival forecasting 1999A neural network model to forecast Japanese demand for travel to Hong Kong

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2024A Sustainable Rental Price Prediction Model Based on Multimodal Input and Deep Learning—Evidence from Airbnb

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Year2019

Typearticle

Published2019-12-02

VenueJournal of Hospitality and Tourism Management

ISSN-L1447-6770

Languageen

Citations64

Files0 public / 0

ShelfForecasting Techniques and Applications

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doi10.1016/j.jhtm.2019.11.003

openalex_workW2993426684

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