A Stochastic Epidemiological SIRD-V Model With LSM-EKF Algorithm for Forecasting and Monitoring the Spread of COVID-19 Pandemic: Real Data
Author:
Affiliation:
1. Laboratoire d’Automatique et Informatique de Guelma (LAIG), Université 8 Mai 1945 Guelma, Guelma, Algeria
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/6287639/10380310/10511052.pdf?arnumber=10511052
Reference39 articles.
1. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
2. A Novel Coronavirus from Patients with Pneumonia in China, 2019
3. Prediction of epidemic trends in COVID-19 with logistic model and machine learning technics
4. Prediction Models for Public Health Containment Measures on COVID-19 Using Artificial Intelligence and Machine Learning: A Systematic Review
5. Deep learning forecasting using time-varying parameters of the SIRD model for Covid-19
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1. Temporal Dynamics and Interplay of Transmission Rate, Vaccination, and Mutation in Epidemic Modeling: A Poisson Point Process Approach;IEEE Transactions on Network Science and Engineering;2024-09
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