Bayesian BILSTM approach for tourism demand forecasting

Citations

Cited by:

1. Feng, Zengxi & Zhang, Xian & Quan, Wei & Liu, Xuefeng & An, Jianhu & Wang, Chang & Ji, Xiuming & Kang, Limin, 2025. "A hybrid deep learning model based on Rime optimization and multi-head attention for cooling load prediction in public buildings," Energy, Elsevier, vol. 339(C).
2. Li, Cheng & Zheng, Weimin & Ge, Peng, 2022. "Tourism demand forecasting with spatiotemporal features," Annals of Tourism Research, Elsevier, vol. 94(C).
3. Sonthalia, Ankit & Femilda Josephin, J.S. & Varuvel, Edwin Geo & Chinnathambi, Arunachalam & Subramanian, Thiyagarajan & Kiani, Farzad, 2025. "A deep learning multi-feature based fusion model for predicting the state of health of lithium-ion batteries," Energy, Elsevier, vol. 317(C).
4. Ghimire, Sujan & Deo, Ravinesh C. & Casillas-Pérez, David & Salcedo-Sanz, Sancho, 2022. "Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise Deep Residual model for short-term multi-step solar radiation prediction," Renewable Energy, Elsevier, vol. 190(C), pages 408-424.
5. Yu, Ling & Zhao, Pengjun & Tang, Junqing & Pang, Liang, 2023. "Changes in tourist mobility after COVID-19 outbreaks," Annals of Tourism Research, Elsevier, vol. 98(C).
6. Zhou, Zhengda & Dai, Yeming & Leng, Mingming, 2025. "A photovoltaic power forecasting framework based on Attention mechanism and parallel prediction architecture," Applied Energy, Elsevier, vol. 391(C).
7. Gergő Thalmeiner & Sándor Gáspár & Ákos Barta & Zoltán Zéman, 2021. "Application of Fuzzy Logic to Evaluate the Economic Impact of COVID-19: Case Study of a Project-Oriented Travel Agency," Sustainability, MDPI, vol. 13(17), pages 1-19, August.
8. Zhang, Chu & Ma, Huixin & Hua, Lei & Sun, Wei & Nazir, Muhammad Shahzad & Peng, Tian, 2022. "An evolutionary deep learning model based on TVFEMD, improved sine cosine algorithm, CNN and BiLSTM for wind speed prediction," Energy, Elsevier, vol. 254(PA).
9. Bhattacharjee, Biplab & Kumar, Rajiv & Senthilkumar, Arunachalam, 2022. "Unidirectional and bidirectional LSTM models for edge weight predictions in dynamic cross-market equity networks," International Review of Financial Analysis, Elsevier, vol. 84(C).
10. Dounia El Bourakadi & Hiba Ramadan & Ali Yahyaouy & Jaouad Boumhidi, 2023. "A robust energy management approach in two-steps ahead using deep learning BiLSTM prediction model and type-2 fuzzy decision-making controller," Fuzzy Optimization and Decision Making, Springer, vol. 22(4), pages 645-667, December.
11. Yong Liu & Xiang-jie Fu & Jeffrey Lin Yi Forrest, 2025. "Forecasting tourism demand with pre-holiday attribute," Information Technology & Tourism, Springer, vol. 27(3), pages 613-648, September.
12. Chien-Jung Ting & Hsing-Mei Juan, 2025. "Assessing the Association of Popular Attractions with Taiwan’s Inbound Tourist Numbers: The Case of Night-Market Keywords," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 15(6), pages 1-4.
13. Mingming Hu & Haifeng Yang & Doris Chenguang Wu & Shuai Ma, 2024. "A novel two-stage combination model for tourism demand forecasting," Tourism Economics, , vol. 30(8), pages 1925-1950, December.
14. Zhen, Hao & Niu, Dongxiao & Wang, Keke & Shi, Yucheng & Ji, Zhengsen & Xu, Xiaomin, 2021. "Photovoltaic power forecasting based on GA improved Bi-LSTM in microgrid without meteorological information," Energy, Elsevier, vol. 231(C).
15. Zheng, Weimin & Huang, Liyao & Lin, Zhibin, 2021. "Multi-attraction, hourly tourism demand forecasting," Annals of Tourism Research, Elsevier, vol. 90(C).
16. Emrah Kocak & Fevzi Okumus & Mehmet Altin, 2023. "Global pandemic uncertainty, pandemic discussion and visitor behaviour: A comparative tourism demand estimation for the US," Tourism Economics, , vol. 29(5), pages 1225-1250, August.
17. Li, Xin & Xu, Yechi & Law, Rob & Wang, Shouyang, 2024. "Enhancing Tourism Demand Forecasting with a Transformer-based Framework," SocArXiv 5ezn3_v1, Center for Open Science.
18. Peng, Tian & Zhang, Chu & Zhou, Jianzhong & Nazir, Muhammad Shahzad, 2021. "An integrated framework of Bi-directional long-short term memory (BiLSTM) based on sine cosine algorithm for hourly solar radiation forecasting," Energy, Elsevier, vol. 221(C).
19. Ming Yin & Feiya Lu & Xingxuan Zhuo & Wangzi Yao & Jialong Liu & Jijiao Jiang, 2024. "Prediction of daily tourism volume based on maximum correlation minimum redundancy feature selection and long short‐term memory network," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 344-365, March.
20. Zhang, Dongxue & Wang, Shuai & Liang, Yuqiu & Du, Zhiyuan, 2023. "A novel combined model for probabilistic load forecasting based on deep learning and improved optimizer," Energy, Elsevier, vol. 264(C).
21. Bi, Jian-Wu & Li, Hui & Fan, Zhi-Ping, 2021. "Tourism demand forecasting with time series imaging: A deep learning model," Annals of Tourism Research, Elsevier, vol. 90(C).
22. Xu, Shilin & Liu, Yang & Jin, Chun, 2023. "Forecasting daily tourism demand with multiple factors," Annals of Tourism Research, Elsevier, vol. 103(C).
23. Li, Xin & Xu, Yechi & Law, Rob & Wang, Shouyang, 2024. "Enhancing tourism demand forecasting with a transformer-based framework," Annals of Tourism Research, Elsevier, vol. 107(C).
24. Amirhossein Amini & Robab Kalantari, 2024. "Gold price prediction by a CNN-Bi-LSTM model along with automatic parameter tuning," PLOS ONE, Public Library of Science, vol. 19(3), pages 1-17, March.
25. Han Liu & Yongjing Wang & Haiyan Song & Ying Liu, 2023. "Measuring tourism demand nowcasting performance using a monotonicity test," Tourism Economics, , vol. 29(5), pages 1302-1327, August.
26. Mohd Sakib & Tamanna Siddiqui & Suhel Mustajab & Reemiah Muneer Alotaibi & Nouf Mohammad Alshareef & Mohammad Zunnun Khan, 2025. "An ensemble deep learning framework for energy demand forecasting using genetic algorithm-based feature selection," PLOS ONE, Public Library of Science, vol. 20(1), pages 1-28, January.