Predicting the impact of the third wave of COVID-19 in India using hybrid statistical machine learning models: A time series forecasting and sentiment analysis …

S Mohan, AK Solanki, HK Taluja, A Singh - Computers in Biology and …, 2022 - Elsevier
Abstract Background Since January 2020, India has faced two waves of COVID-19;
preparation for the upcoming waves is the primary challenge for public health sectors and …

Comparison of ARIMA, ETS, NNAR, TBATS and hybrid models to forecast the second wave of COVID-19 hospitalizations in Italy

G Perone - The European Journal of Health Economics, 2021 - Springer
Abstract The coronavirus disease (COVID-19) is a severe, ongoing, novel pandemic that
emerged in Wuhan, China, in December 2019. As of January 21, 2021, the virus had …

Machine learning and optimization models for supplier selection and order allocation planning

S Islam, SH Amin, LJ Wardley - International Journal of Production …, 2021 - Elsevier
Supplier selection and order allocation have significant roles in supply chain management.
These processes become major challenges when the demand is uncertain. This research …

[HTML][HTML] Explainable Spatio-Temporal Graph Neural Networks for multi-site photovoltaic energy production

A Verdone, S Scardapane, M Panella - Applied Energy, 2024 - Elsevier
In recent years, there has been a growing demand for renewable energy sources, which are
inherently associated with a decentralized distribution and dependent on weather …

A data-driven hybrid ensemble AI model for COVID-19 infection forecast using multiple neural networks and reinforced learning

W Jin, S Dong, C Yu, Q Luo - Computers in Biology and Medicine, 2022 - Elsevier
The COVID-19 outbreak poses a huge challenge to international public health. Reliable
forecast of the number of cases is of great significance to the planning of health resources …

Predicting the trend of indicators related to Covid-19 using the combined MLP-MC model

F Haghighat - Chaos, Solitons & Fractals, 2021 - Elsevier
Although more than a year has passed since the coronavirus outbreak globally, the Covid-
19 pandemic conditions still exist in many countries, including Iran. Predicting the number of …

Forecasting the trends of covid-19 and causal impact of vaccines using bayesian structural time series and arima

M Navas Thorakkattle, S Farhin, AA Khan - Annals of Data Science, 2022 - Springer
Several researchers have used standard time series models to analyze future patterns of
COVID-19 and the Causal impact of vaccinations in various countries. Bayesian structural …

Using the SARIMA model to forecast the fourth global wave of cumulative deaths from COVID-19: Evidence from 12 hard-hit big countries

G Perone - Econometrics, 2022 - mdpi.com
The COVID-19 pandemic is a serious threat to all of us. It has caused an unprecedented
shock to the world's economy, and it has interrupted the lives and livelihood of millions of …

Modelling and forecasting of growth rate of new COVID-19 cases in top nine affected countries: Considering conditional variance and asymmetric effect

A Ekinci - Chaos, Solitons & Fractals, 2021 - Elsevier
COVID-19 pandemic has affected more than a hundred fifty million people and killed over
three million people worldwide over the past year. During this period, different forecasting …

An ensemble machine learning approach for time series forecasting of COVID-19 cases

RR Maaliw, MA Ballera, ZP Mabunga… - 2021 IEEE 12th …, 2021 - ieeexplore.ieee.org
Forecasting assists governments, epidemiologists, and policymakers make calculated
decisions to mitigate the spread of the COVID-19 pandemic, thus saving lives. This paper …