Relevant bibliographies by topics / Hybrid Enhanced Grey Wolf Harris Hawk Optimizer

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Academic literature on the topic 'Hybrid Enhanced Grey Wolf Harris Hawk Optimizer'

Author: Grafiati
Published: 5 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "Hybrid Enhanced Grey Wolf Harris Hawk Optimizer"

1

Devan, P. Arun Mozhi, Rosdiazli Ibrahim, Madiah Omar, Kishore Bingi, and Hakim Abdulrab. "A Novel Hybrid Harris Hawk-Arithmetic Optimization Algorithm for Industrial Wireless Mesh Networks." Sensors 23, no. 13 (2023): 6224. http://dx.doi.org/10.3390/s23136224.

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A novel hybrid Harris Hawk-Arithmetic Optimization Algorithm (HHAOA) for optimizing the Industrial Wireless Mesh Networks (WMNs) and real-time pressure process control was proposed in this research article. The proposed algorithm uses inspiration from Harris Hawk Optimization and the Arithmetic Optimization Algorithm to improve position relocation problems, premature convergence, and the poor accuracy the existing techniques face. The HHAOA algorithm was evaluated on various benchmark functions and compared with other optimization algorithms, namely Arithmetic Optimization Algorithm, Moth Flam
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2

PDGKI, IJCNP. "FSHAHA: Feature Selection using Hybrid Ant Harris Algorithm for IoT Network Security Enhancement." International Journal of Computer Networks & Communications (IJCNC) 17, no. 1 (2025): 978–1. https://doi.org/10.5121/ijcnc.2025.17107.

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Enhancing machine learning model performance involves selecting relevant features, particularly in high-dimensional datasets. This paper proposes a hybrid method named the Multi-Objective Ant Chase algorithm, which integrates Ant Colony Optimization (ACO) and Harris Hawk Optimization (HHO) for effective feature selection. ACO excels at exploring large search spaces using pheromone-guided navigation, while HHO focuses on targeted search with adaptive hunting tactics. Conventional algorithms, such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Grey Wolf Optimizer (GWO), and Monarc
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3

Ouederni, Ramia, and Innocent E. Davidson. "Co-Optimized Design of Islanded Hybrid Microgrids Using Synergistic AI Techniques: A Case Study for Remote Electrification." Energies 18, no. 13 (2025): 3456. https://doi.org/10.3390/en18133456.

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Off-grid and isolated rural communities in developing countries with limited resources require energy supplies for daily residential use and social, economic, and commercial activities. The use of data from space assets and space-based solar power is a feasible solution for addressing ground-based energy insecurity when harnessed in a hybrid manner. Advances in space solar power systems are recognized to be feasible sources of renewable energy. Their usefulness arises due to advances in satellite and space technology, making valuable space data available for smart grid design in these remote a
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4

Tripp-Barba, Carolina, José Alfonso Aguilar-Calderón, Luis Urquiza-Aguiar, Aníbal Zaldívar-Colado, and Alan Ramírez-Noriega. "A Systematic Mapping Study on State Estimation Techniques for Lithium-Ion Batteries in Electric Vehicles." World Electric Vehicle Journal 16, no. 2 (2025): 57. https://doi.org/10.3390/wevj16020057.

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The effective administration of lithium-ion batteries is key to the performance and durability of electric vehicles (EVs). This systematic mapping study (SMS) thoroughly examines optimization methodologies for battery management, concentrating on the estimation of state of health (SoH), remaining useful life (RUL), and state of charge (SoC). The findings disclose various methods that boost the accuracy and reliability of SoC, including enhanced variants of the Kalman filter, machine learning models like long short-term memory (LSTM) and convolutional neural networks (CNNs), as well as hybrid o
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5

Khan, Noman Mujeeb, Abbas Ahmed, Syed Kamran Haider, Muhammad Hamza Zafar, Majad Mansoor, and Naureen Akhtar. "Hybrid General Regression NN Model for Efficient Operation of Centralized TEG System under Non-Uniform Thermal Gradients." Electronics 12, no. 7 (2023): 1688. http://dx.doi.org/10.3390/electronics12071688.

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The global energy demand, along with the proportionate share of renewable energy, is increasing rapidly. Renewables such as thermoelectric generators (TEG) systems have lower power ratings but a highly durable and cost-effective renewable energy technology that can deal with waste heat energy. The main issues associated with TEG systems are related to their vigorous operating conditions. The dynamic temperature gradient across TEG surfaces induces non-uniform temperature distribution (NUTD) that significantly impacts the available output electrical energy. The mismatching current impact may lo
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6

Tu, Binbin, Fei Wang, Yan Huo, and Xiaotian Wang. "A hybrid algorithm of grey wolf optimizer and harris hawks optimization for solving global optimization problems with improved convergence performance." Scientific Reports 13, no. 1 (2023). http://dx.doi.org/10.1038/s41598-023-49754-2.

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AbstractThe grey wolf optimizer is an effective and well-known meta-heuristic algorithm, but it also has the weaknesses of insufficient population diversity, falling into local optimal solutions easily, and unsatisfactory convergence speed. Therefore, we propose a hybrid grey wolf optimizer (HGWO), based mainly on the exploitation phase of the harris hawk optimization. It also includes population initialization with Latin hypercube sampling, a nonlinear convergence factor with local perturbations, some extended exploration strategies. In HGWO, the grey wolves can have harris hawks-like flight
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7

Sani, Hannatu M., A. L. Amoo, and Y. S. Haruna. "Optimal Coordination of Numerical and Directional Over Current Relays using Hybrid Enhanced Grey Wolf Harris Hawk Optimization Algorithm." July 28, 2023. https://doi.org/10.5281/zenodo.8191828.

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Growing demand as a result of the present trend in the world's energy crises is increasingly causing the distribution system to take mesh appearance. As a result, directional overcurrent relays (DOCRs) have become widely used for network coordination, protection and control in both distribution and transmission networks. Efficient and reliable network operation and control, requires optimal coordination of the DOCRs such that the overall operational time is minimized. However, the relay parameter settings must be carefully and optimally chosen (for example, Time Dial settings is bounded be
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8

Houssein, Essam H., Mohamed Hossam Abdel Gafar, Naglaa Fawzy, and Ahmed Y. Sayed. "Recent metaheuristic algorithms for solving some civil engineering optimization problems." Scientific Reports 15, no. 1 (2025). https://doi.org/10.1038/s41598-025-90000-8.

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Abstract In this study, a novel hybrid metaheuristic algorithm, termed (BES–GO), is proposed for solving benchmark structural design optimization problems, including welded beam design, three-bar truss system optimization, minimizing vertical deflection in an I-beam, optimizing the cost of tubular columns, and minimizing the weight of cantilever beams. The performance of the proposed BES–GO algorithm was compared with ten state-of-the-art metaheuristic algorithms: Bald Eagle Search (BES), Growth Optimizer (GO), Ant Lion Optimizer, Tuna Swarm Optimization, Tunicate Swarm Algorithm, Harris Hawk
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9

"FSHAHA: Feature Selection using Hybrid Ant Harris Algorithm for IoT Network Security Enhancement." International journal of Computer Networks & Communications 17, no. 1 (2025): 101–19. https://doi.org/10.5121/ijcnc.2025.17107.

Full text
Abstract:
Enhancing machine learning model performance involves selecting relevant features, particularly in highdimensional datasets. This paper proposes a hybrid method named the Multi-Objective Ant Chase algorithm, which integrates Ant Colony Optimization (ACO) and Harris Hawk Optimization (HHO) for effective feature selection. ACO excels at exploring large search spaces using pheromone-guided navigation, while HHO focuses on targeted search with adaptive hunting tactics. Conventional algorithms, such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Grey Wolf Optimizer (GWO), and Monarch
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10

Mohamed, Mohamed Ahmed Ebrahim, Sayed A. Ward, Mohamed F. El-Gohary, and M. A. Mohamed. "Hybrid fuzzy logic–PI control with metaheuristic optimization for enhanced performance of high-penetration grid-connected PV systems." Scientific Reports 15, no. 1 (2025). https://doi.org/10.1038/s41598-025-09336-w.

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Abstract This paper introduces a hybrid fuzzy logic control-based proportional-integral (FLC-PI) control strategy designed to enhance voltage stability, power quality, and overall performance of central inverters in photovoltaic power plants (PVPPs). The study is based on a real-world PVPP with an installed capacity of 26.136 MWp, connected to the Egyptian national grid at Fares City, Kom Ombo Centre, Aswan Governorate. A user-friendly MATLAB/SIMULINK environment is developed, incorporating eleven distinct blocks along with a modelled national utility grid, utilizing actual operational data fr
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