Forecasting of COVID-19 using deep layer Recurrent Neural Networks (RNNs) with Gated Recurrent Units (GRUs) and Long Short-Term Memory (LSTM) cells-Reference-Cited by-同舟云学术

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Forecasting of COVID-19 using deep layer Recurrent Neural Networks (RNNs) with Gated Recurrent Units (GRUs) and Long Short-Term Memory (LSTM) cells

Published:2021-05 Issue: Volume:146 Page:110861
ISSN:0960-0779
Container-title:Chaos, Solitons & Fractals
language:en
Short-container-title:Chaos, Solitons & Fractals

Author:

ArunKumar K.E.,Kalaga Dinesh V.,Kumar Ch. Mohan Sai,Kawaji Masahiro,Brenza Timothy M

Publisher

Elsevier BV

Subject

General Mathematics,General Physics and Astronomy,Statistical and Nonlinear Physics,Applied Mathematics

Reference55 articles.

1. WHO declares COVID-19 a pandemic;Cucinotta;Acta bio-medica: Atenei Parmensis,2020

2. Worldometers.info. 2020 https://www.worldometers.info/.

3. Role of Intelligent Computing in COVID-19 Prognosis: A State-of-the-Art Review;rekhaHanumanthu,2020

4. Prediction of the number of deaths in India due to SARS-CoV-2 at 5–6 weeks;Ghosal,2020

5. A Python based Support Vector Regression Model for prediction of Covid 19 cases in India;Parbat,2020

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