Secure distance based multi-objective artificial rabbits algorithm for clustering and routing in cognitive radio network DOI Open Access

KN Shyleshchandra Gudihatti,

K Pradeep Kumar

International Journal of Advanced Technology and Engineering Exploration, Год журнала: 2023, Номер 10(108)

Опубликована: Ноя. 30, 2023

Recent developments have been made in the field of cognitive radio that involve equipment due to its spectrum access capacity [1].The concept was first introduced by Joseph Mitola III 1999 [2].Cognitive networks (CRN) represent a revolutionary approach wireless communication systems.CRNs find applications scenarios where is underutilized, such as rural areas, and dynamic environments conditions change rapidly.Potential include broadband access, smart grids [3], emergency systems, etc. CRN contain two users, namely, primary users (PUs) secondary (SUs) [4].

Язык: Английский

Optimizing energy Dynamics: A comprehensive analysis of hybrid energy storage systems integrating battery banks and supercapacitors DOI
Aykut Fatih Güven, Almoataz Y. Abdelaziz, Mohamed Mahmoud Samy

и другие.

Energy Conversion and Management, Год журнала: 2024, Номер 312, С. 118560 - 118560

Опубликована: Май 20, 2024

Язык: Английский

Процитировано

78

Distance-based mutual congestion feature selection with genetic algorithm for high-dimensional medical datasets DOI
Hossein Nematzadeh, Joseph Mani,

Zahra Nematzadeh

и другие.

Neural Computing and Applications, Год журнала: 2025, Номер unknown

Опубликована: Янв. 10, 2025

Язык: Английский

Процитировано

3

Dynamic fitness-distance balance-based artificial rabbits optimization algorithm to solve optimal power flow problem DOI
Hüseyin Bakır

Expert Systems with Applications, Год журнала: 2023, Номер 240, С. 122460 - 122460

Опубликована: Ноя. 9, 2023

Язык: Английский

Процитировано

31

Advances in Artificial Rabbits Optimization: A Comprehensive Review DOI

Ferzat Anka,

Nazim Agaoglu,

Sajjad Nematzadeh

и другие.

Archives of Computational Methods in Engineering, Год журнала: 2024, Номер unknown

Опубликована: Дек. 7, 2024

Язык: Английский

Процитировано

7

V-shaped and S-shaped binary artificial protozoa optimizer (APO) algorithm for wrapper feature selection on biological data DOI Creative Commons
Amir Seyyedabbasi, Gang Hu, Hisham A. Shehadeh

и другие.

Cluster Computing, Год журнала: 2025, Номер 28(3)

Опубликована: Янв. 21, 2025

Язык: Английский

Процитировано

1

Adaptive dynamic elite opposition-based Ali Baba and the forty thieves algorithm for high-dimensional feature selection DOI
Malik Braik, Mohammed A. Awadallah, Hussein Al-Zoubi

и другие.

Cluster Computing, Год журнала: 2024, Номер 27(8), С. 10487 - 10523

Опубликована: Май 6, 2024

Язык: Английский

Процитировано

6

Parameter extraction of proton exchange membrane fuel cell based on artificial rabbits’ optimization algorithm and conducting laboratory tests DOI Creative Commons
Faisal B. Baz, Ragab A. El‐Sehiemy,

Ahmed Saeed Abdelrazek Bayoumi

и другие.

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Сен. 10, 2024

Язык: Английский

Процитировано

4

Augmented electric eel foraging optimization algorithm for feature selection with high-dimensional biological and medical diagnosis DOI
Mohammed Azmi Al‐Betar, Malik Braik, Elfadil A. Mohamed

и другие.

Neural Computing and Applications, Год журнала: 2024, Номер unknown

Опубликована: Сен. 18, 2024

Язык: Английский

Процитировано

4

Multi-strategy fusion pelican optimization algorithm and logic operation ensemble of transfer functions for high-dimensional feature selection problems DOI

Hao-Ming Song,

Jie-Sheng Wang,

Jia-Ning Hou

и другие.

International Journal of Machine Learning and Cybernetics, Год журнала: 2025, Номер unknown

Опубликована: Янв. 17, 2025

Язык: Английский

Процитировано

0

Newton Downhill Optimizer for Global Optimization DOI Creative Commons

Wanting Xiao,

Kaichen Ouyang, Junbo Lian

и другие.

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Апрель 1, 2025

Abstract The study presents the Newton's Downhill Optimizer (NDO), a novel metaheuristic algorithm designed to address challenges of complex, high-dimensional, and nonlinear optimization problems. Mathematical-Based Algorithms (MBAs) are category algorithms based on mathematical principles. They widely applied in numerical computation, symbolic manipulation, geometric processing, problems, probabilistic statistics, offering efficient precise solutions complex Inspired by Method, NDO combines its precision with downhill strategy stochastic processes, specifically real-world applications benchmark method inspired enhancing capability exploring solution space escaping local optima. In tests, demonstrated exceptional performance, surpassing majority competing multiple test suites CEC 2017 2022. We conducted comprehensive comparison against 14 well-established algorithms. These include mathematical-based approaches such as AOA, SCHO, SCA, SABO, NRBO, RUN. also compared it classical like CMA-ES, ABC, DE, PSO. Additionally, we included advanced recently published WSO, EHO, FDB_AGDEand GQPSO. results demonstrate that outperforms most these It exhibits superior convergence speed remarkable stability.In engineering applications, outperformed other reducer design task step-cone pulley delivered outstanding disk clutch brake tasks. A significant contribution is application breast cancer feature selection, tested two Breast datasets. performance accuracy, sensitivity, specificity, Matthews Correlation Coefficient (MCC), achieving accuracy across This underscores potential viable tool for addressing both medical fields. source codes will be shared at https://github.com/oykc1234/NDO.

Язык: Английский

Процитировано

0