An Overview of the Artificial Neural Network-Based Applications and Impact Assessment in COVID-19

Abstract

The article is regarding infectious disease, which has been affecting people all around the world since December 2019. Write-up gives a brief introduction of the Coronavirus from its emergence to the final solution of its exit. It gives us a glimpse of the biological structure of the virus, precautions to be taken in care to reduce the spread of the disease. The description shows us the consequences of the virus-like the mortality rate and the life expectancy rate. The article also presents a few vaccines development projects as a whole to fight COVID-19. It also describes the efficacy of vaccination and the post-vaccination symptoms. In the end, the write-up presents real-time neural network-based applications to fight COVID-19 and a few machine learning and deep learning techniques to diagnose a COVID-19 infected person. The final part of the article concludes with an artificial neural network and statistical neural network-based approaches to identify the rate of infection risk in a country.

Stochastic Levenberg–Marquardt Neural Network Implementation for Analyzing the Convective Heat Transfer in a Wavy Fin

“…A multilayer perceptron network model is trained in the current study to predict the results of the heat transfer analysis of the wavy fin. An ANN is a three-layer (input, hidden, and output layers) feedforward neural network architecture [39,40]. An input layer is composed of many neurons.…”