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.
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Binary whale optimization algorithm with logarithmic decreasing time-varying modified sigmoid transfer function for descriptor selection problem.pdf Restricted to Repository staff only Download (7MB) |
Abstract
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.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | ATS drug classification, Binary whale optimization algorithm, Modified logarithmic decreasing time-varying update technique, Time-varying transfer function |
| Divisions: | Faculty Of Electronics And Computer Technology And Engineering |
| Depositing User: | Maizatul Najwa Ahmad |
| Date Deposited: | 20 Sep 2024 09:49 |
| Last Modified: | 20 Sep 2024 09:49 |
| URI: | http://eprints.utem.edu.my/id/eprint/27879 |
| Statistic Details: | View Download Statistic |
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