Tool life prediction of dicing saw based on adaptive golden jackal optimizing GRU DOI

Wanyong Liang,

Wei Zhu, Yanyan Zhang

et al.

International Journal on Interactive Design and Manufacturing (IJIDeM), Journal Year: 2023, Volume and Issue: 18(2), P. 1059 - 1074

Published: Dec. 12, 2023

Language: Английский

A Systematic Review of the Whale Optimization Algorithm: Theoretical Foundation, Improvements, and Hybridizations DOI Open Access
Mohammad H. Nadimi-Shahraki, Hoda Zamani, Zahra Asghari Varzaneh

et al.

Archives of Computational Methods in Engineering, Journal Year: 2023, Volume and Issue: 30(7), P. 4113 - 4159

Published: May 27, 2023

Language: Английский

Citations

121
Transforming sentiment analysis for e-commerce product reviews: Hybrid deep learning model with an innovative term weighting and feature selection DOI

Punithavathi Rasappan,

M. Premkumar, Garima Sinha

et al.

Information Processing & Management, Journal Year: 2024, Volume and Issue: 61(3), P. 103654 - 103654

Published: Jan. 30, 2024

Language: Английский

Citations

19
A comprehensive and systematic literature review on intrusion detection systems in the internet of medical things: current status, challenges, and opportunities DOI Creative Commons
Arezou Naghib,

Farhad Soleimanian Gharehchopogh,

Azadeh Zamanifar

et al.

Artificial Intelligence Review, Journal Year: 2025, Volume and Issue: 58(4)

Published: Jan. 30, 2025

Language: Английский

Citations

3
Copula entropy-based golden jackal optimization algorithm for high-dimensional feature selection problems DOI
Heba Askr, Mahmoud Abdel-Salam, Aboul Ella Hassanien

et al.

Expert Systems with Applications, Journal Year: 2023, Volume and Issue: 238, P. 121582 - 121582

Published: Sept. 19, 2023

Language: Английский

Citations

41
An Improved Golden Jackal Optimization Algorithm Based on Multi-strategy Mixing for Solving Engineering Optimization Problems DOI
Jun Wang, Wenchuan Wang, Kwok‐wing Chau

et al.

Journal of Bionic Engineering, Journal Year: 2024, Volume and Issue: 21(2), P. 1092 - 1115

Published: Feb. 28, 2024

Language: Английский

Citations

14
Ameliorated Golden jackal optimization (AGJO) with enhanced movement and multi-angle position updating strategy for solving engineering problems DOI
Jianfu Bai, Samir Khatir, Laith Abualigah

et al.

Advances in Engineering Software, Journal Year: 2024, Volume and Issue: 194, P. 103665 - 103665

Published: May 15, 2024

Language: Английский

Citations

9
Improving golden jackel optimization algorithm: An application of chemical data classification DOI
Aiedh Mrisi Alharthi, Dler Hussein Kadir, Abdo Mohammed Al‐Fakih

et al.

Chemometrics and Intelligent Laboratory Systems, Journal Year: 2024, Volume and Issue: 250, P. 105149 - 105149

Published: May 17, 2024

Language: Английский

Citations

9
A novel deep learning framework based swin transformer for dermal cancer cell classification DOI

K. Ramkumar,

Elias Paulino Medeiros,

Ani Dong

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2024, Volume and Issue: 133, P. 108097 - 108097

Published: March 13, 2024

Language: Английский

Citations

6
Refinement of Dynamic Hunting Leadership Algorithm for Enhanced Numerical Optimization DOI Creative Commons

Oluwatayomi Rereloluwa Adegboye,

Afi Kekeli Feda, Opeoluwa Seun Ojekemi

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 103271 - 103298

Published: Jan. 1, 2024

A recently created optimization algorithm named the Dynamic Hunting Leadership (DHL) was inspired by leadership tactics used in hunting operations. The foundation of DHL is idea that successful can significantly increase endeavors. Although has shown to be relatively simple and tackling a variety practical issues, it been discovered suffers with efficiently balancing global exploration local search phase, particularly high-dimensional numerical problems engineering applications. Furthermore, due drawbacks, vulnerable becoming stuck optimal. present study aims tackle aforementioned challenges introducing modified variant DHL, referred as mDHL, utilizes Levy Flight technique localized development strategy augment each hunter's capacity track their prey attain superior optimal outcomes. Moreover, escape operator quasi-opposition learning are synergistically incorporated foster hunters' techniques. These knowledge sharing between leaders hunters, resulting harmonious blend capabilities. mDHL outperform existing optimizers across 20 function test suites varying dimensions from 30 200 CEC 2019 functions. In addition, successfully applied solve four design cases, demonstrating its practicality. experimental findings indicate substantial improvement over conventional emphasizing potential competitive efficient for addressing challenges.

Language: Английский

Citations

5
Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm DOI Creative Commons
M. Premkumar,

R. Sowmya,

S. Kavitha

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Sept. 9, 2024

Language: Английский

Citations

5