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Forecasting Tourist Arrivals via Random Forest and Long Short-term Memory · Study

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ArticleForecasting Tourist Arrivals via Random Forest and Long Short-term Memory

Lu Peng2020

Article2020

Forecasting Tourist Arrivals via Random Forest and Long Short-term Memory

Lu Peng · Lin Wang · Xue-Yi Ai · Yu‐Rong Zeng

67 citations·0/0 files stored·Cognitive Computation

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Forecasting Techniques and Applications Stock Market Forecasting Methods Time Series Analysis and Forecasting

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References

2017Deep learning with long short-term memory networks for financial market predictions 2018Forecasting the volatility of stock price index: A hybrid model integrating LSTM with multiple GARCH-type models 2018Forecasting tourist arrivals with machine learning and internet search index 2017Big Data sources and methods for social and economic analyses 2013Forecasting tourism demand to Catalonia: Neural networks vs. time series models 2018Effective tourist volume forecasting supported by PCA and improved BPNN using Baidu index 2016The Baidu Index: Uses in predicting tourism flows –A case study of the Forbidden City 2015The influence of tourism website on tourists' behavior to determine destination selection: A case study of creative economy in Korea

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2021Tourism demand forecasting and tourists’ search behavior: evidence from segmented Baidu search volume

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Year2020

Typearticle

Published2020-06-25

VenueCognitive Computation

ISSN-L1866-9956

Languageen

Citations67

Files0 public / 0

ShelfForecasting Techniques and Applications

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doi10.1007/s12559-020-09747-z

openalex_workW3037596256

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