Gradient-based grey wolf optimizer with Gaussian walk: Application in modelling and prediction of the COVID-19 pandemic

Date

2021-09-01

Author

Khalilpourazari, Soheyl
Hashemi Doulabi, Hossein
Özyüksel Çiftçioğlu, Aybike
Weber, Gerhard-Wilhelm

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This research proposes a new type of Grey Wolf optimizer named Gradient-based Grey Wolf Optimizer (GGWO). Using gradient information, we accelerated the convergence of the algorithm that enables us to solve well-known complex benchmark functions optimally for the first time in this field. We also used the Gaussian walk and Lévy flight to improve the exploration and exploitation capabilities of the GGWO to avoid trapping in local optima. We apply the suggested method to several benchmark functions to show its efficiency. The outcomes reveal that our algorithm performs superior to most existing algorithms in the literature in most benchmarks. Moreover, we apply our algorithm for predicting the COVID-19 pandemic in the US. Since the prediction of the epidemic is a complicated task due to its stochastic nature, presenting efficient methods to solve the problem is vital. Since the healthcare system has a limited capacity, it is essential to predict the pandemic's future trend to avoid overload. Our results predict that the US will have almost 16 million cases by the end of November. The upcoming peak in the number of infected, ICU admitted cases would be mid-to-end November. In the end, we proposed several managerial insights that will help the policymakers have a clearer vision about the growth of COVID-19 and avoid equipment shortages in healthcare systems.

Subject Keywords

COVID-19, Pandemic modeling, Grey wolf optimizer, Gradient search

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85105694711&origin=inward
https://hdl.handle.net/11511/90814

Journal

Expert Systems with Applications

DOI

https://doi.org/10.1016/j.eswa.2021.114920

Collections

Graduate School of Applied Mathematics, Article

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Citation Formats

S. Khalilpourazari, H. Hashemi Doulabi, A. Özyüksel Çiftçioğlu, and G.-W. Weber, “Gradient-based grey wolf optimizer with Gaussian walk: Application in modelling and prediction of the COVID-19 pandemic,” Expert Systems with Applications, pp. 0–0, 2021, Accessed: 00, 2021. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85105694711&origin=inward.