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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...

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Main Authors: Ahmed, Marzia, Mohd Herwan, Sulaiman, Ahmad Johari, Mohamad
Format: Article
Language:English
Published: Sciendo 2023
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/37860/1/Improved%20barnacle%20mating%20optimizer-based%20least%20square%20support%20vector%20machine.pdf
http://umpir.ump.edu.my/id/eprint/37860/
https://doi.org/10.2478/cait-2023-0007
https://doi.org/10.2478/cait-2023-0007
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spelling my.ump.umpir.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
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
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
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.
format Article
author Ahmed, Marzia
Mohd Herwan, Sulaiman
Ahmad Johari, Mohamad
author_facet Ahmed, Marzia
Mohd Herwan, Sulaiman
Ahmad Johari, Mohamad
author_sort Ahmed, Marzia
title 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_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_sort improved barnacle mating optimizer-based least square support vector machine to predict covid-19 confirmed cases with total vaccination
publisher Sciendo
publishDate 2023
url http://umpir.ump.edu.my/id/eprint/37860/1/Improved%20barnacle%20mating%20optimizer-based%20least%20square%20support%20vector%20machine.pdf
http://umpir.ump.edu.my/id/eprint/37860/
https://doi.org/10.2478/cait-2023-0007
https://doi.org/10.2478/cait-2023-0007
_version_ 1822923533846577152
score 13.232414

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