Improved barnacle mating optimizer-based least square support vector machine to predict COVID-19 confirmed cases with total vaccination
Every country must have an accurate and efficient forecasting model to avoid and manage the epidemic. This paper suggests an upgrade to one of the evolutionary algorithms inspired by nature, the Barnacle Mating Optimizer (BMO). First, the exploration phase of the original BMO is enhanced by enforcin...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2023
|
| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/37860/ http://umpir.ump.edu.my/id/eprint/37860/1/Improved%20barnacle%20mating%20optimizer-based%20least%20square%20support%20vector%20machine.pdf |
| _version_ | 1848825364748435456 |
|---|---|
| author | Ahmed, Marzia Mohd Herwan, Sulaiman Ahmad Johari, Mohamad |
| author_facet | Ahmed, Marzia Mohd Herwan, Sulaiman Ahmad Johari, Mohamad |
| author_sort | Ahmed, Marzia |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Every country must have an accurate and efficient forecasting model to avoid and manage the epidemic. This paper suggests an upgrade to one of the evolutionary algorithms inspired by nature, the Barnacle Mating Optimizer (BMO). First, the exploration phase of the original BMO is enhanced by enforcing and replacing the sperm cast equation through Levy flight. Then, the Least Square Support Vector Machine (LSSVM) is partnered with the improved BMO (IBMO). This hybrid approach, IBMO-LSSVM, has been deployed effectively for time-series forecasting to enhance the RBF kernel-based LSSVM model since vaccination started against COVID-19 in Malaysia. In comparison to other well-known algorithms, our outcomes are superior. In addition, the IBMO is assessed on 19 conventional benchmarks and the IEEE Congress of Evolutionary Computation Benchmark Test Functions (CECC06, 2019 Competition). In most cases, IBMO outputs are better than comparison algorithms. However, in other circumstances, the outcomes are comparable. |
| first_indexed | 2025-11-15T03:27:45Z |
| format | Article |
| id | ump-37860 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:27:45Z |
| publishDate | 2023 |
| publisher | Sciendo |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-378602023-06-26T02:56:45Z http://umpir.ump.edu.my/id/eprint/37860/ Improved barnacle mating optimizer-based least square support vector machine to predict COVID-19 confirmed cases with total vaccination Ahmed, Marzia Mohd Herwan, Sulaiman Ahmad Johari, Mohamad TK Electrical engineering. Electronics Nuclear engineering Every country must have an accurate and efficient forecasting model to avoid and manage the epidemic. This paper suggests an upgrade to one of the evolutionary algorithms inspired by nature, the Barnacle Mating Optimizer (BMO). First, the exploration phase of the original BMO is enhanced by enforcing and replacing the sperm cast equation through Levy flight. Then, the Least Square Support Vector Machine (LSSVM) is partnered with the improved BMO (IBMO). This hybrid approach, IBMO-LSSVM, has been deployed effectively for time-series forecasting to enhance the RBF kernel-based LSSVM model since vaccination started against COVID-19 in Malaysia. In comparison to other well-known algorithms, our outcomes are superior. In addition, the IBMO is assessed on 19 conventional benchmarks and the IEEE Congress of Evolutionary Computation Benchmark Test Functions (CECC06, 2019 Competition). In most cases, IBMO outputs are better than comparison algorithms. However, in other circumstances, the outcomes are comparable. Sciendo 2023-03 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/37860/1/Improved%20barnacle%20mating%20optimizer-based%20least%20square%20support%20vector%20machine.pdf Ahmed, Marzia and Mohd Herwan, Sulaiman and Ahmad Johari, Mohamad (2023) Improved barnacle mating optimizer-based least square support vector machine to predict COVID-19 confirmed cases with total vaccination. Cybernetics and Information Technologies, 23 (1). 125 -140. ISSN 1311-9702. (Published) https://doi.org/10.2478/cait-2023-0007 https://doi.org/10.2478/cait-2023-0007 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Ahmed, Marzia Mohd Herwan, Sulaiman Ahmad Johari, Mohamad Improved barnacle mating optimizer-based least square support vector machine to predict COVID-19 confirmed cases with total vaccination |
| title | Improved barnacle mating optimizer-based least square support vector machine to predict COVID-19 confirmed cases with total vaccination |
| title_full | Improved barnacle mating optimizer-based least square support vector machine to predict COVID-19 confirmed cases with total vaccination |
| title_fullStr | Improved barnacle mating optimizer-based least square support vector machine to predict COVID-19 confirmed cases with total vaccination |
| title_full_unstemmed | Improved barnacle mating optimizer-based least square support vector machine to predict COVID-19 confirmed cases with total vaccination |
| title_short | Improved barnacle mating optimizer-based least square support vector machine to predict COVID-19 confirmed cases with total vaccination |
| title_sort | improved barnacle mating optimizer-based least square support vector machine to predict covid-19 confirmed cases with total vaccination |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/37860/ http://umpir.ump.edu.my/id/eprint/37860/ http://umpir.ump.edu.my/id/eprint/37860/ http://umpir.ump.edu.my/id/eprint/37860/1/Improved%20barnacle%20mating%20optimizer-based%20least%20square%20support%20vector%20machine.pdf |