Prediction of COVID-19 confirmed cases combining deep learning methods and Bayesian optimization
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DOI: 10.1016/j.chaos.2020.110511
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- Shruti Sharma & Yogesh Kumar Gupta & Abhinava K. Mishra, 2023. "Analysis and Prediction of COVID-19 Multivariate Data Using Deep Ensemble Learning Methods," IJERPH, MDPI, vol. 20(11), pages 1-23, May.
- Khan, Junaid Iqbal & Ullah, Farman & Lee, Sungchang, 2022. "Attention based parameter estimation and states forecasting of COVID-19 pandemic using modified SIQRD Model," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).
- Zhao, Xinxing & Li, Kainan & Ang, Candice Ke En & Cheong, Kang Hao, 2023. "A deep learning based hybrid architecture for weekly dengue incidences forecasting," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
- Xue-Bo Jin & Wei-Zhen Zheng & Jian-Lei Kong & Xiao-Yi Wang & Yu-Ting Bai & Ting-Li Su & Seng Lin, 2021. "Deep-Learning Forecasting Method for Electric Power Load via Attention-Based Encoder-Decoder with Bayesian Optimization," Energies, MDPI, vol. 14(6), pages 1-18, March.
- Aryan Bhambu & Arabin Kumar Dey, 2024. "Some variation of COBRA in sequential learning setup," Papers 2405.04539, arXiv.org.
- Ali, Furqan & Ullah, Farman & Khan, Junaid Iqbal & Khan, Jebran & Sardar, Abdul Wasay & Lee, Sungchang, 2023. "COVID-19 spread control policies based early dynamics forecasting using deep learning algorithm," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
- Yong-Ju Jang & Min-Seung Kim & Chan-Ho Lee & Ji-Hye Choi & Jeong-Hee Lee & Sun-Hong Lee & Tae-Eung Sung, 2022. "A Novel Approach on Deep Learning—Based Decision Support System Applying Multiple Output LSTM-Autoencoder: Focusing on Identifying Variations by PHSMs’ Effect over COVID-19 Pandemic," IJERPH, MDPI, vol. 19(11), pages 1-22, June.
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Keywords
COVID-19; Deep learning; Multi-head attention; CNN; LSTM; Bayesian optimization;All these keywords.
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