Quantitative structure-property relationship modelling for predicting retention indices of essential oils based on an improved horse herd optimization algorithm
The horse herd optimization algorithm (HOA), one of the more contemporary metaheuristic algorithms, has demonstrated superior performance in a number of challenging optimization tasks. In the present work, the descriptor selection issue is resolved by classifying different essential oil retention in...
Saved in:
Main Authors: | Alharthi, Aiedh Mrisi, Kadir, Dler Hussein, Al-Fakih, Abdo Mohammed, Algamal, Zakariya Y., Al-Thanoon, Niam Abdulmunim, Khalid Qasim, Maimoonah |
---|---|
Format: | Article |
Published: |
Taylor & Francis Group
2023
|
Subjects: | |
Online Access: | http://eprints.utm.my/106730/ http://dx.doi.org/10.1080/1062936X.2023.2261855 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
QSAR classification model for diverse series of antifungal agents based on binary coyote optimization algorithm
by: Mohammed Al-Fakih, Abdo, et al.
Published: (2023) -
Weighted L1-norm logistic regression for gene selection of microarray gene expression classification
by: Alharthi, Aiedh Mrisi, et al.
Published: (2020) -
Gene selection and classification of microarray gene expression data based on a new adaptive L1-norm elastic net penalty
by: Alharthi, Aiedh Mrisi, et al.
Published: (2021) -
Improving penalized logistic regression model with missing values in high-dimensional data
by: Alharthi, Aiedh Mrisi, et al.
Published: (2022) -
Embedded feature selection methods with high dimensionality for elastic net and logistic regression models
by: Alharthi, Aiedh Mrisi
Published: (2022)