[HTML][HTML] Nonlinear neural network based forecasting model for predicting COVID-19 cases
S Namasudra, S Dhamodharavadhani… - Neural processing …, 2023 - Springer
The recent COVID-19 outbreak has severely affected people around the world. There is a
need of an efficient decision making tool to improve awareness about the spread of COVID …
need of an efficient decision making tool to improve awareness about the spread of COVID …
[HTML][HTML] Time series forecasting of COVID-19 transmission in Asia Pacific countries using deep neural networks
The novel human coronavirus disease COVID-19 has become the fifth documented
pandemic since the 1918 flu pandemic. COVID-19 was first reported in Wuhan, China, and …
pandemic since the 1918 flu pandemic. COVID-19 was first reported in Wuhan, China, and …
Forecasting the prevalence of COVID-19 outbreak in Egypt using nonlinear autoregressive artificial neural networks
AI Saba, AH Elsheikh - Process safety and environmental protection, 2020 - Elsevier
Abstract SARS-CoV-2 (COVID-19) is a new Coronavirus, with first reported human infections
in late 2019. COVID-19 has been officially declared as a universal pandemic by the World …
in late 2019. COVID-19 has been officially declared as a universal pandemic by the World …
Machine learning approaches for covid-19 forecasting
O Istaiteh, T Owais, N Al-Madi… - … conference on intelligent …, 2020 - ieeexplore.ieee.org
COVID-19 (Coronavirus) pandemic tends to be one of the most global serious issues in the
last century. Furthermore, the world did not face any similar experience regarding the spread …
last century. Furthermore, the world did not face any similar experience regarding the spread …
Time series predicting of COVID-19 based on deep learning
COVID-19 was declared a global pandemic by the World Health Organisation (WHO) on
11th March 2020. Many researchers have, in the past, attempted to predict a COVID …
11th March 2020. Many researchers have, in the past, attempted to predict a COVID …
[HTML][HTML] Comparative analysis of Gated Recurrent Units (GRU), long Short-Term memory (LSTM) cells, autoregressive Integrated moving average (ARIMA), seasonal …
Several machine learning and deep learning models were reported in the literature to
forecast COVID-19 but there is no comprehensive report on the comparison between …
forecast COVID-19 but there is no comprehensive report on the comparison between …
[HTML][HTML] COVID-19 mortality rate prediction for India using statistical neural network models
S Dhamodharavadhani, R Rathipriya… - Frontiers in Public …, 2020 - frontiersin.org
The primary aim of this study is to investigate suitable Statistical Neural Network (SNN)
models and their hybrid version for COVID-19 mortality prediction in Indian populations and …
models and their hybrid version for COVID-19 mortality prediction in Indian populations and …
[HTML][HTML] ARIMA and NAR based prediction model for time series analysis of COVID-19 cases in India
In this paper, we have applied the univariate time series model to predict the number of
COVID-19 infected cases that can be expected in upcoming days in India. We adopted an …
COVID-19 infected cases that can be expected in upcoming days in India. We adopted an …
Forecasting of COVID-19 using deep layer recurrent neural networks (RNNs) with gated recurrent units (GRUs) and long short-term memory (LSTM) cells
In December 2019, first case of the COVID-19 was reported in Wuhan, Hubei province in
China. Soon world health organization has declared contagious coronavirus disease (aka …
China. Soon world health organization has declared contagious coronavirus disease (aka …
COVID‐19 pandemic forecasting using CNN‐LSTM: a hybrid approach
ZM Zain, NM Alturki - Journal of Control Science and …, 2021 - Wiley Online Library
COVID‐19 has sparked a worldwide pandemic, with the number of infected cases and
deaths rising on a regular basis. Along with recent advances in soft computing technology …
deaths rising on a regular basis. Along with recent advances in soft computing technology …