Multi-objective Harris Hawk metaheuristic algorithms for the diagnosis of Parkinson’s disease DOI Creative Commons
Tansel Dökeroğlu, Tayfun Küçükyılmaz

Expert Systems with Applications, Год журнала: 2025, Номер 270, С. 126503 - 126503

Опубликована: Янв. 16, 2025

Язык: Английский

Arctic puffin optimization: A bio-inspired metaheuristic algorithm for solving engineering design optimization DOI
Wenchuan Wang,

Wei-can Tian,

Dong-mei Xu

и другие.

Advances in Engineering Software, Год журнала: 2024, Номер 195, С. 103694 - 103694

Опубликована: Июнь 15, 2024

Язык: Английский

Процитировано

49

Novel hybrid kepler optimization algorithm for parameter estimation of photovoltaic modules DOI Creative Commons
Reda Mohamed, Mohamed Abdel‐Basset, Karam M. Sallam

и другие.

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

Опубликована: Фев. 11, 2024

Abstract The parameter identification problem of photovoltaic (PV) models is classified as a complex nonlinear optimization that cannot be accurately solved by traditional techniques. Therefore, metaheuristic algorithms have been recently used to solve this due their potential approximate the optimal solution for several complicated problems. Despite that, existing still suffer from sluggish convergence rates and stagnation in local optima when applied tackle problem. study presents new estimation technique, namely HKOA, based on integrating published Kepler algorithm (KOA) with ranking-based update exploitation improvement mechanisms estimate unknown parameters third-, single-, double-diode models. former mechanism aims at promoting KOA’s exploration operator diminish getting stuck optima, while latter strengthen its faster converge solution. Both KOA HKOA are validated using RTC France solar cell five PV modules, including Photowatt-PWP201, Ultra 85-P, STP6-120/36, STM6-40/36, show efficiency stability. In addition, they extensively compared techniques effectiveness. According experimental findings, strong alternative method estimating because it can yield substantially different superior findings

Язык: Английский

Процитировано

24

An advanced deep reinforcement learning algorithm for three-layer D2D-edge-cloud computing architecture for efficient task offloading in the Internet of Things DOI
Komeil Moghaddasi, Shakiba Rajabi, Farhad Soleimanian Gharehchopogh

и другие.

Sustainable Computing Informatics and Systems, Год журнала: 2024, Номер 43, С. 100992 - 100992

Опубликована: Май 1, 2024

Язык: Английский

Процитировано

21

Multi-objective liver cancer algorithm: A novel algorithm for solving engineering design problems DOI Creative Commons
Kanak Kalita, Janjhyam Venkata Naga Ramesh, Róbert Čep

и другие.

Heliyon, Год журнала: 2024, Номер 10(5), С. e26665 - e26665

Опубликована: Март 1, 2024

This research introduces the Multi-Objective Liver Cancer Algorithm (MOLCA), a novel approach inspired by growth and proliferation patterns of liver tumors. MOLCA emulates evolutionary tendencies tumors, leveraging their expansion dynamics as model for solving multi-objective optimization problems in engineering design. The algorithm uniquely combines genetic operators with Random Opposition-Based Learning (ROBL) strategy, optimizing both local global search capabilities. Further enhancement is achieved through integration elitist non-dominated sorting (NDS), information feedback mechanism (IFM) Crowding Distance (CD) selection method, which collectively aim to efficiently identify Pareto optimal front. performance rigorously assessed using comprehensive set standard test benchmarks, including ZDT, DTLZ various Constraint (CONSTR, TNK, SRN, BNH, OSY KITA) real-world design like Brushless DC wheel motor, Safety isolating transformer, Helical spring, Two-bar truss Welded beam. Its efficacy benchmarked against prominent algorithms such grey wolf optimizer (NSGWO), multiobjective multi-verse (MOMVO), (NSGA-II), decomposition-based (MOEA/D) marine predator (MOMPA). Quantitative analysis conducted GD, IGD, SP, SD, HV RT metrics represent convergence distribution, while qualitative aspects are presented graphical representations fronts. source code available at: https://github.com/kanak02/MOLCA.

Язык: Английский

Процитировано

20

Meta-heuristics and deep learning for energy applications: Review and open research challenges (2018–2023) DOI Creative Commons

Eghbal Hosseini,

Abbas M. Al-Ghaili, Dler Hussein Kadir

и другие.

Energy Strategy Reviews, Год журнала: 2024, Номер 53, С. 101409 - 101409

Опубликована: Май 1, 2024

The synergy between deep learning and meta-heuristic algorithms presents a promising avenue for tackling the complexities of energy-related modeling forecasting tasks. While excels in capturing intricate patterns data, it may falter achieving optimality due to nonlinear nature energy data. Conversely, offer optimization capabilities but suffer from computational burdens, especially with high-dimensional This paper provides comprehensive review spanning 2018 2023, examining integration within frameworks applications. We analyze state-of-the-art techniques, innovations, recent advancements, identifying open research challenges. Additionally, we propose novel framework that seamlessly merges into paradigms, aiming enhance performance efficiency addressing problems. contributions include: 1. Overview advancements MHs, DL, integration. 2. Coverage trends 2023. 3. Introduction Alpha metric evaluation. 4. Innovative harmonizing MHs DL

Язык: Английский

Процитировано

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

и другие.

Artificial Intelligence Review, Год журнала: 2025, Номер 58(4)

Опубликована: Янв. 30, 2025

Язык: Английский

Процитировано

7

An Energy-Efficient Data Offloading Strategy for 5G-Enabled Vehicular Edge Computing Networks Using Double Deep Q-Network DOI
Komeil Moghaddasi, Shakiba Rajabi, Farhad Soleimanian Gharehchopogh

и другие.

Wireless Personal Communications, Год журнала: 2023, Номер 133(3), С. 2019 - 2064

Опубликована: Дек. 1, 2023

Язык: Английский

Процитировано

25

An improved multi-strategy Golden Jackal algorithm for real world engineering problems DOI
Mohamed Elhoseny, Mahmoud Abdel-Salam,

Ibrahim M. El‐Hasnony

и другие.

Knowledge-Based Systems, Год журнала: 2024, Номер 295, С. 111725 - 111725

Опубликована: Апрель 16, 2024

Язык: Английский

Процитировано

17

Orthogonal opposition-based learning honey badger algorithm with differential evolution for global optimization and engineering design problems DOI Creative Commons
Peixin Huang, Yongquan Zhou, Wu Deng

и другие.

Alexandria Engineering Journal, Год журнала: 2024, Номер 91, С. 348 - 367

Опубликована: Фев. 19, 2024

Honey badger algorithm (HBA) is a recent swarm-based metaheuristic that excels in simplicity and high exploitation capability. However, it suffers from some limitations including weak exploration capacity an imbalance between exploitation. In this paper, improved honey called ODEHBA proposed to improve the performance of basic HBA. Firstly, orthogonal opposition-based learning technique employed assist population escaping local optimum. Secondly, differential evolution utilized ensure enrichment diversity enhance convergence speed. Finally, capability boosted by equilibrium pool strategy. To validate efficacy ODEHBA, compared with 13 well-known algorithms on CEC2022 benchmark test sets. Friedman Wilcoxon rank-sum are assess ODEHBA. Furthermore, three engineering design problems Internet Vehicles (IoV) routing problem applied The simulation results demonstrate solving complex numerical problems, design, IoV problems. This holds significant practical implications for cost reduction resource utilization.

Язык: Английский

Процитировано

14

Advancing Network Security in Industrial IoT: A Deep Dive into AI-Enabled Intrusion Detection Systems DOI
Mohammad Shahin,

Mazdak Maghanaki,

Ali Hosseinzadeh

и другие.

Advanced Engineering Informatics, Год журнала: 2024, Номер 62, С. 102685 - 102685

Опубликована: Июль 12, 2024

Язык: Английский

Процитировано

14