Open Access

ARTICLE

An Intelligent Fine-Tuned Forecasting Technique for Covid-19 Prediction Using Neuralprophet Model

Savita Khurana¹, Gaurav Sharma², Neha Miglani³, Aman Singh⁴, Abdullah Alharbi⁵, Wael Alosaimi⁵, Hashem Alyami⁶, Nitin Goyal^7,*

1 Information Technology Department, Seth Jai Parkash Mukand Lal Institute of Engineering and Technology, Radaur, Haryana, India
2 Computer Science & Engineering Department, Seth Jai Parkash Mukand Lal Institute of Engineering and Technology, Radaur, Haryana, India
3 Computer Engineering Department, National Institute of Technology, Kurukshetra, Haryana, India
4 Computer Science & Engineering Department, Lovely Professional University, Jalandhar, Punjab, India
5 Department of Information Technology, College of Computers and Information Technology, Taif University, P. O. Box 11099, Taif 21944, Saudi Arabia
6 Department of Computer Science, College of Computers and Information Technology, Taif University, P. O. Box 11099, Taif 21944, Saudi Arabia
7 Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India

* Corresponding Author: Nitin Goyal. Email:

Computers, Materials & Continua 2022, 71(1), 629-649. https://doi.org/10.32604/cmc.2022.021884

Received 17 July 2021; Accepted 18 August 2021; Issue published 03 November 2021

Abstract

COVID-19, being the virus of fear and anxiety, is one of the most recent and emergent of various respiratory disorders. It is similar to the MERS-COV and SARS-COV, the viruses that affected a large population of different countries in the year 2012 and 2002, respectively. Various standard models have been used for COVID-19 epidemic prediction but they suffered from low accuracy due to lesser data availability and a high level of uncertainty. The proposed approach used a machine learning-based time-series Facebook NeuralProphet model for prediction of the number of death as well as confirmed cases and compared it with Poisson Distribution, and Random Forest Model. The analysis upon dataset has been performed considering the time duration from January 1^st 2020 to16^th July 2021. The model has been developed to obtain the forecast values till September 2021. This study aimed to determine the pandemic prediction of COVID-19 in the second wave of coronavirus in India using the latest Time-Series model to observe and predict the coronavirus pandemic situation across the country. In India, the cases are rapidly increasing day-by-day since mid of Feb 2021. The prediction of death rate using the proposed model has a good ability to forecast the COVID-19 dataset essentially in the second wave. To empower the prediction for future validation, the proposed model works effectively.

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