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A High‐Performance MPPT Solution for Solar DC Microgrids: Leveraging the Hippopotamus Algorithm for Greater Efficiency and Stability
Published 2025-05-01“…Performance of HA's is compared with three established optimization algorithms: Grey Wolf Optimization, Cuckoo Search Algorithm and Particle‐Swarm Optimization across different operating scenarios and partial shading circumstances. …”
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An efficient metaheuristic optimization algorithm for optimal power extraction from PV systems under various weather and load-changing conditions
Published 2025-09-01“…A comprehensive study compares the HHO technique with established methods such as perturb and observe (P&O), modified P&O (MP&O), incremental conductance (IC), Spline MPPT, particle swarm optimization (PSO), grasshopper optimization (GHO), and grey wolf optimization (GWO) across fast-changing irradiance, partial shading, complex partial shading, and load-changing conditions. …”
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Comparison of Maximum Power Point Tracking Methods Using Metaheuristic Optimization Algorithms for Photovoltaic Systems
Published 2021-08-01“…In this study, simulation studies has been carried out for two different partially shaded scenarios using the boost-type DC-DC converter and MPPT algorithm in the PV array consisting of 3 panels connected in series. …”
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Design and Analysis of a Hybrid MPPT Method for PV Systems Under Partial Shading Conditions
Published 2025-06-01“…The classical Maximum Power Point Tracking (MPPT) algorithm fails to determine the global maximum operating point to prevent power losses under partial shading conditions. …”
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Optimizing solar maximum power point tracking with adaptive PSO: A comparative analysis of inertia weight and acceleration coefficient strategies
Published 2025-09-01“…However, conventional MPPT techniques, such as Perturb and Observe (P&O), often suffer from power losses, slow convergence, and poor performance under partial shading conditions (PSC). Metaheuristic algorithms such as Particle Swarm Optimization (PSO) are explored extensively for MPPT applications. …”
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27
Fault localization for automatic train operation based on the adaptive error locating array algorithm
Published 2025-01-01“…Then the Partial Variable Intensity Covering Array (PVICA) algorithm is used to generate the initial set of test cases, and the cases are executed sequentially. …”
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Asset management using an extended Markowitz theorem
Published 2014-06-01“…The resulted model is an NP-Hard problem and the proposed study uses two metaheuristics, namely genetic algorithm (GA) and particle swarm optimization (PSO) to find efficient solutions. …”
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A novel global MPPT method based on sooty tern optimization for photovoltaic systems under complex partial shading
Published 2025-07-01“…Abstract As the deployment of photovoltaic (PV) systems continues to expand globally, the need for robust and highly efficient Maximum Power Point Tracking (MPPT) algorithms becomes increasingly critical, particularly under complex Partial Shading Conditions (PSC) where multiple local maxima can significantly reduce energy yield. …”
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Hybridization of deep learning models with crested porcupine optimizer algorithm-based cybersecurity detection on industrial IoT for smart city environments
Published 2025-08-01“…To accomplish that, the CCPOA-HDLM method comprises distinct processes such as min-max normalization, improved Salp swarm algorithm (ISSA)-based feature selection, Multi-Channel Convolutional Neural Network - Recurrent Neural Network (MCNN-RNN)-based cybersecurity detection, and crested porcupine optimizer (CPO)-based parameter selection process. …”
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Nature-inspired MPPT algorithms for solar PV and fault classification using deep learning techniques
Published 2024-12-01“…To select the best optimization model for MPPT under PSC, the nature-inspired dragonfly algorithm (DA), moth flame optimization algorithm (MFOA), grasshopper optimization algorithm (GOA), and salp swarm optimization algorithm (SSOA) are used in this work to evaluate the tracking efficiency (TE) of the solar PV systems. …”
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Multi-Peak Photovoltaic Maximum Power Point Tracking Method Based on Honey Badger Algorithm Under Localized Shading Conditions
Published 2025-03-01“…The performance of this method is also compared and analyzed with the traditional MPPT methods based on the perturbation observation (P&O) method and Particle Swarm Optimization (PSO) algorithm. The experimental results have proven that, compared with the MPPT methods based on P&O and PSO, the proposed multi-peak MPPT method based on the HBA algorithm has a faster tracking speed, higher tracking accuracy, and fewer iterations.…”
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High-efficiency MPPT Using ZVS quasi-resonant converter and PSO algorithm: Simulation and PIL validation
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Classification of biomedical lung cancer images using optimized binary bat technique by constructing oblique decision trees
Published 2025-05-01“…In this paper, we propose a novel structural formation of the oblique decision tree (OBT) using a swarm intelligence technique, namely, the Binary Bat Swarm Algorithm (BBSA). …”
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Heterogeneous Multi-Agent Deep Reinforcement Learning for Cluster-Based Spectrum Sharing in UAV Swarms
Published 2025-05-01“…The MAPPO-H enables the CHs to decide cluster selection and moving position, while CMs utilize IPPO-M to cluster autonomously under the condition of certain partial channel distribution information (CDI). Adequate experimental evidence has confirmed that the HMDRL-UC algorithm proposed in this paper is not only capable of managing dynamic drone swarm scenarios in the presence of partial CDI, but also has a clear advantage over the other existing three algorithms in terms of average throughput, intra-cluster communication delay, and minimum signal-to-noise ratio (SNR).…”
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Task Offloading and Data Compression Collaboration Optimization for UAV Swarm-Enabled Mobile Edge Computing
Published 2025-04-01“…To address this issue, we propose a UAV swarm-enabled MEC system that integrates data compression technology, in which the only swarm head UAV (USH) offloads the compressed computing tasks compressed by the UEs and partially distributes them to the swarm member UAV (USM) for collaborative processing. …”
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Reducing PAPR in NOMA Waveforms Using Genetic-Enhanced PTS and SLM: A Low-Complexity Approach for Improved throughput, power spectral density, and Power Efficiency
Published 2025-06-01“…To overcome these issues, this paper introduces new Particle Swarm Optimization (PSO)-improved partial transmit sequence (PTS) and Selective Mapping (SLM) schemes that optimally choose phase factors with much lower search complexity. …”
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Fractional-Order Predictive Functional Control of Industrial Processes with Partial Actuator Failures
Published 2020-01-01“…The comprehensive simulation results demonstrate the performance of the proposed control method by comparing with a recently developed predictive functional control, genetic algorithm, and particle swarm optimization-based versions in terms of four performance indices.…”
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Investigation on Photovoltaic Array Modeling and the MPPT Control Method under Partial Shading Conditions
Published 2021-01-01“…Its main idea is to determine the initial position of particles and remove the acceleration factor and random number in traditional particle swarm optimization (PSO) algorithm. Additionally, according to the distance between two consecutive peak points, the maximum value of velocity is obtained. …”
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