Using Epidemic Modeling, Machine Learning and Control Feedback Strategy for Policy Management of COVID-19-Reference-Cited by-同舟云学术

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Using Epidemic Modeling, Machine Learning and Control Feedback Strategy for Policy Management of COVID-19

Published:2022 Issue: Volume:10 Page:98244-98258
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Narayan Kartik¹,Rathore Heena²^ORCID,Znidi Faycal³^ORCID

Affiliation:

1. Department of Computer Science and Engineering, Indian Institute of Technology Jodhpur, Jodhpur, India

2. Department of Computer Science, Texas State University, San Marcos, TX, USA

3. Department of Electrical Engineering, Texas A&M University Texarkana, Texarkana, TX, USA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09893130.pdf?arnumber=9893130

Reference52 articles.

1. Remark on “algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound constrained optimization”

2. Threshold behaviour of a stochastic SIR model

3. Complexity of the Basic Reproduction Number (R0)

4. Modelling COVID-19

5. COVID-19 Social Distance Proximity Estimation Using Machine Learning Analyses of Smartphone Sensor Data

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Controlling a Pandemic: An Account of Successfully Applying Control Theory to the Covid-19 Pandemic in Denmark [Applications of Control];IEEE Control Systems;2023-08

2. CSS Quarter-Century Members [Member Activities];IEEE Control Systems;2023-08

3. Epidemic Modeling using Hybrid of Time-varying SIRD, Particle Swarm Optimization, and Deep Learning;2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT);2023-07-06

4. Multi-weight susceptible-infected model for predicting COVID-19 in China;Neurocomputing;2023-05

5. Machine Learning Techniques for Disease Prediction;ITM Web of Conferences;2023

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