Dr. Junaid Farooq

A deep learning algorithm for modeling and forecasting of COVID-19 in five worst affected states of India

Junaid Farooq, Mohammad Abid Bazaz

Alexandria Engineering Journal, 2021, 60(1), 587–596 · Peer-reviewed

In brief

A deep learning model that forecasts the spread of COVID-19 in the five Indian states hit hardest in 2020.

The five Indian states with the most COVID-19 cases at the time of the study.
The five Indian states with the most COVID-19 cases at the time of the study.

Abstract

In this paper, deep learning is employed to propose an Artificial Neural Network (ANN) based online incremental learning technique for developing an adaptive and non-intrusive analytical model of Covid-19 pandemic to analyze the temporal dynamics of the disease spread. The model is able to intelligently adapt to new ground realities in real-time eliminating the need to retrain the model from scratch every time a new data set is received from the continuously evolving training data. The model is validated with the historical data and a forecast of the disease spread for 30-days is given in the five worst affected states of India.

Cite this paper

@article{farooq2021a,
  title   = {A deep learning algorithm for modeling and forecasting of COVID-19 in five worst affected states of India},
  author  = {Farooq, Junaid and Bazaz, Mohammad Abid},
  journal = {Alexandria Engineering Journal},
  year    = {2021},
  volume  = {60(1)},
  pages   = {587--596},
  doi     = {10.1016/j.aej.2020.09.037},
}

Topic: Scientific machine learning

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