A novel nonlinear time‑varying sigmoid transfer function in binary whale optimization algorithm for descriptors selection in drug classifcation

Mohd Yusof, Norfadzlia and Muda, Azah Kamilah and Pratama, Satrya Fajri and Abraham, Ajith (2022) A novel nonlinear time‑varying sigmoid transfer function in binary whale optimization algorithm for descriptors selection in drug classifcation. Molecular Diversity, 27. pp. 71-80. ISSN 1381-1991

Text
MOLECULAR_DIVERSITY_ONLINE-NORFADZLIA-PAPER2.PDF
Restricted to Registered users only
Download (1MB)

Official URL: https://link.springer.com/article/10.1007/s11030-0...

Abstract

In computational chemistry, the high-dimensional molecular descriptors contribute to the curse of dimensionality issue. Binary whale optimization algorithm (BWOA) is a recently proposed metaheuristic optimization algorithm that has been efficiently applied in feature selection. The main contribution of this paper is a new version of the nonlinear time-varying Sigmoid transfer function to improve the exploitation and exploration activities in the standard whale optimization algorithm (WOA). A new BWOA algorithm, namely BWOA-3, is introduced to solve the descriptors selection problem, which becomes the second contribution. To validate BWOA-3 performance, a high-dimensional drug dataset is employed. The proficiency of the proposed BWOA-3 and the comparative optimization algorithms are measured based on convergence speed, the length of the selected feature subset, and classification performance (accuracy, specificity, sensitivity, and f-measure). In addition, statistical significance tests are also conducted using the Friedman test and Wilcoxon signed-rank test. The comparative optimization algorithms include two BWOA variants, binary bat algorithm (BBA), binary gray wolf algorithm (BGWOA), and binary manta-ray foraging algorithm (BMRFO). As the final contribution, from all experiments, this study has successfully revealed the superiority of BWOA-3 in solving the descriptors selection problem and improving the Amphetamine-type Stimulants (ATS) drug classification performance.

Item Type:	Article
Uncontrolled Keywords:	Metaheuristic, Feature selection, Descriptors selection, Time-varying transfer function, Binary whale optimization algorithm
Divisions:	Faculty of Electrical and Electronic Engineering Technology
Depositing User:	mr eiisaa ahyead
Date Deposited:	14 Apr 2023 14:56
Last Modified:	14 Apr 2023 14:56
URI:	http://eprints.utem.edu.my/id/eprint/26775
Statistic Details:	View Download Statistic

Actions (login required)

View Item