A deep learning approach for daily tourist flow forecasting with consumer search data-Reference-Cited by-同舟云学术

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A deep learning approach for daily tourist flow forecasting with consumer search data

Published:2020-01-05 Issue:3 Volume:25 Page:323-339
ISSN:1094-1665
Container-title:Asia Pacific Journal of Tourism Research
language:en
Short-container-title:Asia Pacific Journal of Tourism Research

Author:

Zhang Binru¹^ORCID,Li Nao²,Shi Feng³,Law Rob⁴^ORCID

Affiliation:

1. School of Finance and Economics, Yangtze Normal University, Chongqing, People’s Republic of China

2. Tourism College of Beijing Union University, Beijing, People’s Republic of China

3. School of Business Administration, Baise University, Guangxi, People’s Republic of China

4. School of Hotel & Tourism Management, The Hong Kong Polytechnic University, Kowloon, Hong Kong

Publisher

Informa UK Limited

Subject

Tourism, Leisure and Hospitality Management,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10941665.2019.1709876

Reference51 articles.

1. Time Series Forecasting Techniques: Short‐term Planning in Tourism

2. Learning Deep Architectures for AI

3. Learning long-term dependencies with gradient descent is difficult

5. Application of SVR with chaotic GASA algorithm to forecast Taiwanese 3G mobile phone demand

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