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Binary whale optimization algorithm with logarithmic decreasing time-varying modified sigmoid transfer function for descriptor selection problem

In cheminformatics, choosing the right descriptors is a crucial step in improving predictive models, particularly those that use machine learning algorithms. Recently, researchers in cheminformatics have been lured to swarm intelligence to optimize the process of discovering relevant descriptors in...

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Main Authors: Yusof, Norfadzlia Mohd, Muda, Azah Kamilah, Pratama, Satrya Fajri, Carbo-Dorca, Ramon, Abraham, Ajith
Format: Conference or Workshop Item
Language:English
Published: 2023
Online Access:http://eprints.utem.edu.my/id/eprint/27879/1/Binary%20whale%20optimization%20algorithm%20with%20logarithmic%20decreasing%20time-varying%20modified%20sigmoid%20transfer%20function%20for%20descriptor%20selection%20problem.pdf
http://eprints.utem.edu.my/id/eprint/27879/
https://link.springer.com/chapter/10.1007/978-3-031-27524-1_65
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spelling my.utem.eprints.278792024-09-20T09:49:15Z http://eprints.utem.edu.my/id/eprint/27879/ Binary whale optimization algorithm with logarithmic decreasing time-varying modified sigmoid transfer function for descriptor selection problem Yusof, Norfadzlia Mohd Muda, Azah Kamilah Pratama, Satrya Fajri Carbo-Dorca, Ramon Abraham, Ajith In cheminformatics, choosing the right descriptors is a crucial step in improving predictive models, particularly those that use machine learning algorithms. Recently, researchers in cheminformatics have been lured to swarm intelligence to optimize the process of discovering relevant descriptors in the wrapper feature selection. This work introduced a new Binary Whale Optimization Algorithm, which utilized a novel time-varying modified Sigmoid transfer function with a modified logarithmic decreasing time-varying update strategy to improve the balancing of exploration and exploitation in WOA. The new Binary Whale Optimization Algorithm is integrated with wrapper feature selection and validated on descriptor selection problem to improve Amphetamine-type stimulants drug classification result. The suggested approach is compared to well-known swarm intelligence algorithms, and the results demonstrate its superiority. 2023 Conference or Workshop Item PeerReviewed text en http://eprints.utem.edu.my/id/eprint/27879/1/Binary%20whale%20optimization%20algorithm%20with%20logarithmic%20decreasing%20time-varying%20modified%20sigmoid%20transfer%20function%20for%20descriptor%20selection%20problem.pdf Yusof, Norfadzlia Mohd and Muda, Azah Kamilah and Pratama, Satrya Fajri and Carbo-Dorca, Ramon and Abraham, Ajith (2023) Binary whale optimization algorithm with logarithmic decreasing time-varying modified sigmoid transfer function for descriptor selection problem. In: 14th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2022, and the 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2022, 14 December 2022through 16 December 2022, Virtual, Online. https://link.springer.com/chapter/10.1007/978-3-031-27524-1_65
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
description In cheminformatics, choosing the right descriptors is a crucial step in improving predictive models, particularly those that use machine learning algorithms. Recently, researchers in cheminformatics have been lured to swarm intelligence to optimize the process of discovering relevant descriptors in the wrapper feature selection. This work introduced a new Binary Whale Optimization Algorithm, which utilized a novel time-varying modified Sigmoid transfer function with a modified logarithmic decreasing time-varying update strategy to improve the balancing of exploration and exploitation in WOA. The new Binary Whale Optimization Algorithm is integrated with wrapper feature selection and validated on descriptor selection problem to improve Amphetamine-type stimulants drug classification result. The suggested approach is compared to well-known swarm intelligence algorithms, and the results demonstrate its superiority.
format Conference or Workshop Item
author Yusof, Norfadzlia Mohd
Muda, Azah Kamilah
Pratama, Satrya Fajri
Carbo-Dorca, Ramon
Abraham, Ajith
spellingShingle Yusof, Norfadzlia Mohd
Muda, Azah Kamilah
Pratama, Satrya Fajri
Carbo-Dorca, Ramon
Abraham, Ajith
Binary whale optimization algorithm with logarithmic decreasing time-varying modified sigmoid transfer function for descriptor selection problem
author_facet Yusof, Norfadzlia Mohd
Muda, Azah Kamilah
Pratama, Satrya Fajri
Carbo-Dorca, Ramon
Abraham, Ajith
author_sort Yusof, Norfadzlia Mohd
title Binary whale optimization algorithm with logarithmic decreasing time-varying modified sigmoid transfer function for descriptor selection problem
title_short Binary whale optimization algorithm with logarithmic decreasing time-varying modified sigmoid transfer function for descriptor selection problem
title_full Binary whale optimization algorithm with logarithmic decreasing time-varying modified sigmoid transfer function for descriptor selection problem
title_fullStr Binary whale optimization algorithm with logarithmic decreasing time-varying modified sigmoid transfer function for descriptor selection problem
title_full_unstemmed Binary whale optimization algorithm with logarithmic decreasing time-varying modified sigmoid transfer function for descriptor selection problem
title_sort binary whale optimization algorithm with logarithmic decreasing time-varying modified sigmoid transfer function for descriptor selection problem
publishDate 2023
url http://eprints.utem.edu.my/id/eprint/27879/1/Binary%20whale%20optimization%20algorithm%20with%20logarithmic%20decreasing%20time-varying%20modified%20sigmoid%20transfer%20function%20for%20descriptor%20selection%20problem.pdf
http://eprints.utem.edu.my/id/eprint/27879/
https://link.springer.com/chapter/10.1007/978-3-031-27524-1_65
_version_ 1811599517109190656
score 13.211869

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