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

Junaid Farooq | Zendy; Mohammad Abid Bazaz | Zendy

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

Author(s) -

Junaid Farooq,

Mohammad Abid Bazaz

Publication year - 2020

Publication title -

alexandria engineering journal

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.584

H-Index - 58

eISSN - 2090-2670

pISSN - 1110-0168

DOI - 10.1016/j.aej.2020.09.037

Subject(s) - covid-19 , artificial neural network , computer science , artificial intelligence , set (abstract data type) , deep learning , data set , pandemic , machine learning , training set , data mining , infectious disease (medical specialty) , disease , medicine , pathology , programming language , virology , outbreak , biology

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 most affected states of India.

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