Zuriani, Mustaffa and Mohd Herwan, Sulaiman (2021) Covid-19 confirmed cases prediction in china based on barnacles mating optimizer-least squares support vector machines. Cybernetics and Information Technologies, 21 (4). pp. 62-76. ISSN 1311-9702. (Published)
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Abstract
The Covid19 has significantly changed the global landscape in every aspect including economy, social life, and many others. After almost two years of living with the pandemic, new challenges are faced by the research community. It may take some time before the world can be declared as totally safe from the virus. Therefore, prediction of Covid19 confirmed cases is vital for the sake of proper prevention and precaution steps. In this study, a hybrid Barnacles Mating Optimizer with Least Square Support Vector Machines (BMO-LSSVM) is proposed for prediction of Covid19 confirmed cases. The employed data are the Covid19 cases in China which are defined in daily periodicity. The BMO was utilized to obtain optimal values of LSSVM hyper-parameters. Later, with the optimized values of the hyper-parameters, the prediction task will be executed by LSSVM. Through the experiments, the study recommends the superiority of BMO-LSSVM over the other identified hybrid algorithms.
| Item Type: | Article |
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| Additional Information: | Indexed by Scopus |
| Uncontrolled Keywords: | Barnacles mating optimizer; Machine learning; Meta-Heuristic; Optimization; Time series prediction |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Faculty/Division: | Faculty of Computing Faculty of Electrical and Electronic Engineering Technology |
| Depositing User: | Mr Muhamad Firdaus Janih@Jaini |
| Date Deposited: | 31 May 2022 01:39 |
| Last Modified: | 31 May 2022 01:39 |
| URI: | http://umpir.ump.edu.my/id/eprint/33077 |
| Download Statistic: | View Download Statistics |
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