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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-12-01
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| Series: | Systems and Soft Computing |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772941923000200 |
| _version_ | 1797389368167497728 |
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| author | Riya Karmakar Sandip Chatterjee Debabrata Datta Dipankar Chakraborty |
| author_facet | Riya Karmakar Sandip Chatterjee Debabrata Datta Dipankar Chakraborty |
| author_sort | Riya Karmakar |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-08T22:54:50Z |
| format | Article |
| id | doaj.art-c8721a8418394154aed52cbbfddeae97 |
| institution | Directory Open Access Journal |
| issn | 2772-9419 |
| language | English |
| last_indexed | 2024-03-08T22:54:50Z |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Systems and Soft Computing |
| spelling | doaj.art-c8721a8418394154aed52cbbfddeae972023-12-16T06:11:27ZengElsevierSystems and Soft Computing2772-94192024-12-016200067Application of harmony search algorithm in optimizing autoregressive integrated moving average: A study on a data set of Coronavirus Disease 2019Riya Karmakar0Sandip Chatterjee1Debabrata Datta2Dipankar Chakraborty3Department of Mathematics, Heritage Institute of Technology, Kolkata 700107, IndiaDepartment of Mathematics, Heritage Institute of Technology, Kolkata 700107, India; Corresponding author.Department of Information Technology, Heritage Institute of Technology, Kolkata 700107, IndiaDepartment of Mathematics, Heritage Institute of Technology, Kolkata 700107, IndiaWorld 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.http://www.sciencedirect.com/science/article/pii/S2772941923000200ForecastingARIMAMetaheuristicsHarmony searchAugmented Dickey–Fuller testCOVID-19 |
| spellingShingle | Riya Karmakar Sandip Chatterjee Debabrata Datta Dipankar Chakraborty Application of harmony search algorithm in optimizing autoregressive integrated moving average: A study on a data set of Coronavirus Disease 2019 Systems and Soft Computing Forecasting ARIMA Metaheuristics Harmony search Augmented Dickey–Fuller test COVID-19 |
| title | Application of harmony search algorithm in optimizing autoregressive integrated moving average: A study on a data set of Coronavirus Disease 2019 |
| title_full | Application of harmony search algorithm in optimizing autoregressive integrated moving average: A study on a data set of Coronavirus Disease 2019 |
| title_fullStr | Application of harmony search algorithm in optimizing autoregressive integrated moving average: A study on a data set of Coronavirus Disease 2019 |
| title_full_unstemmed | Application of harmony search algorithm in optimizing autoregressive integrated moving average: A study on a data set of Coronavirus Disease 2019 |
| title_short | Application of harmony search algorithm in optimizing autoregressive integrated moving average: A study on a data set of Coronavirus Disease 2019 |
| title_sort | application of harmony search algorithm in optimizing autoregressive integrated moving average a study on a data set of coronavirus disease 2019 |
| topic | Forecasting ARIMA Metaheuristics Harmony search Augmented Dickey–Fuller test COVID-19 |
| url | http://www.sciencedirect.com/science/article/pii/S2772941923000200 |
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