Application of harmony search algorithm in optimizing autoregressive integrated moving average: A study on a data set of Coronavirus Disease 2019

World Health Organization (WHO) declared Coronavirus Disease 2019 (COVID-19), caused by the virus named Severe Acute Respiratory Syndrome Corona Virus-2 (SARS-CoV-2), as a global pandemic on March 11, 2020. Several researchers have used various statistical models and techniques to study and forecast...

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Bibliographic Details
Main Authors: Riya Karmakar, Sandip Chatterjee, Debabrata Datta, Dipankar Chakraborty
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Systems and Soft Computing
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Online Access:http://www.sciencedirect.com/science/article/pii/S2772941923000200
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Summary:World Health Organization (WHO) declared Coronavirus Disease 2019 (COVID-19), caused by the virus named Severe Acute Respiratory Syndrome Corona Virus-2 (SARS-CoV-2), as a global pandemic on March 11, 2020. Several researchers have used various statistical models and techniques to study and forecast the trend of spread and magnitude of the impact of SARS-CoV-2. ARIMA is one such model that has been widely used for this purpose, but in most cases, the model was not optimized suitably. In this paper, a music-inspired metaheuristic optimization algorithm, named Harmony Search (HS), has been integrated with ARIMA in order to improve the forecasting of the COVID-19 data set. The accuracy of forecasting has significantly increased after optimizing the model using the proposed algorithm. Furthermore, a novel application of HS has also been discussed in this paper.
ISSN:2772-9419