The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.
Deep learning methods for forecasting COVID-19 time-Series data: A Comparative study
Open accessAbstract
Highlights • Developed deep learning methods to forecast the COVID19 spread.• Five deep learning models have been compared for COVID-19 forecasting.• Time-series COVID19 data from Italy, Spain, France, China, the USA, and Australia are used.• Results demonstrate the potential of deep learning models to forecast COVID19 data.• Results show the superior performance of the Variational AutoEncoder model.
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Cites
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Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
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Cited by
Deep learning modelling techniques: Current progress, applications, advantages, and challenges
Ahmed, S. F., Alam, M. S. B., Hassan, M., Rozbu, M. R., Ishtiak, T., Rafa, N., Mofijur, M., Shawkat Ali, A. B. M., & Gandomi, A. H. (2023) · Artificial Intelligence Review · doi:10.1007/s10462-023-10466-8 · Cited by 1,079
Deep Learning for Time Series Forecasting: A Survey
Torres, J. F., Hadjout, D., Sebaa, A., Martínez-Álvarez, F., & Troncoso, A. (2021) · Big Data · doi:10.1089/big.2020.0159 · Cited by 818
Deep Learning applications for COVID-19
Shorten, C., Khoshgoftaar, T. M., & Furht, B. (2021) · Journal of Big Data · doi:10.1186/s40537-020-00392-9 · Cited by 350
Applications of artificial intelligence in battling against covid-19: A literature review
Tayarani N., M.-H. (2021) · Chaos, Solitons & Fractals · doi:10.1016/j.chaos.2020.110338 · Cited by 210
Forecasting covid-19 new cases using deep learning methods
Xu, L., Magar, R., & Barati Farimani, A. (2022) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2022.105342 · Cited by 105
Metadata
- Authors
- Zeroual, A., Harrou, F., Dairi, A., & Sun, Y.
- Venue
- Chaos, Solitons & Fractals
- Publisher
- Elsevier BV
- Published
- 2020-11
- Volume
- 140
- Pages
- 110121
- ISSN
- 0960-0779 (ISSN-L)
- OpenAlex
- W3042316884
- Cited by
- 508
- References
- 46
- FWCI
- 14.01
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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