K.E. ArunKumar

Comparative analysis of Gated Recurrent Units (GRU), long Short-Term memory (LSTM) cells, autoregressive Integrated moving average (ARIMA), seasonal autoregressive Integrated moving average (SARIMA) for forecasting COVID-19 trends

K.E. ArunKumar, Dinesh V. Kalaga, Ch. Mohan Sai Kumar et al. · Alexandria Engineering Journal · 2022 · 244 citations · Full text

Forecasting the dynamics of cumulative COVID-19 cases (confirmed, recovered and deaths) for top-16 countries using statistical machine learning models: Auto-Regressive Integrated Moving Average (ARIMA) and Seasonal Auto-Regressive Integrated Moving Average (SARIMA)

K.E. ArunKumar, Dinesh V. Kalaga, Ch. Mohan Sai Kumar et al. · Applied Soft Computing · 2021 · 237 citations · Full text

Statistical Machine, Top-16 Countries, Predictive Analytics +11

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

K.E. ArunKumar, Dinesh V. Kalaga, Ch. Mohan Sai Kumar et al. · Chaos Solitons & Fractals · 2021 · 233 citations · Full text

Forecasting Methodology, Engineering, Long Covid +7

Maleic anhydride-functionalized graphene nanofillers render epoxy coatings highly resistant to corrosion and microbial attack

Govinda Chilkoor, Roman Sarder, Jamil Islam et al. · Carbon · 2019 · 57 citations

Materials Science, Graphene Nanomeshes, Engineering +9

Scale-up of a downflow bubble column: Experimental investigations

Dinesh V. Kalaga, Manizheh Ansari, Damon E. Turney et al. · Chemical Engineering Journal · 2019 · 19 citations · Full text

Cavitating Flow, Bubble Dynamic, Engineering +4