Distributed hybrid energy storage photovoltaic microgrid control based on MPPT algorithm and equilibrium control strategy by Yanlong Qi, Rui Liu, Haisheng Lin, Junchen Zhong, Zhen Chen

“…However, current photovoltaic microgrids suffer from unstable output and power fluctuations. To improve the stability and system controllability of photovoltaic microgrid output, this study constructs an optimized grey wolf optimization algorithm. …”
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Performance Evaluation of Hybrid Bio-Inspired and Deep Learning Algorithms in Gene Selection and Cancer Classification by Shahad S. Alkamli, Hala M. Alshamlan

“…Our findings reveal that hybrid bio-inspired methods, such as Grey Wolf Optimizer and Harris Hawks Optimization, achieve high classification accuracy with minimal selected genes, making them computationally efficient for clinical applications. …”
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Ensemble machine learning algorithm for cost-effective and timely detection of diabetes in Maiduguri, Borno State by Emmanuel Gbenga Dada, Aishatu Ibrahim Birma, Abdulkarim Abbas Gora

“…The proposed WAEL model ingeniously combines five feature spaces through the grey wolf optimisation (GWO) algorithm to uncover the optimal weight combination. …”
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Optimized CNN-LSTM with hybrid metaheuristic approaches for solar radiation forecasting by İrem Fatma Şener, İhsan Tuğal

“…The performance of several machine learning and deep learning models, including Long Short-Term Memory, Autoregressive Integrated Moving Average, Multilayer Perceptron, Random Forest, XGBoost, Support Vector Regression, and a hybrid CNN-LSTM model, is evaluated for daily solar radiation forecasting. To improve the accuracy of the model, hyperparameter optimization is applied to the CNN-LSTM model using three metaheuristic algorithms: Particle Swarm Optimization, Grey Wolf Optimization, and Starfish Optimization Algorithm. …”
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Enhancing CNN-based network intrusion detection through hyperparameter optimization by Antanios Kaissar, Ali Bou Nassif, Bassel Soudan, MohammadNoor Injadat

“…Four distinct optimization techniques, including Grid Search (GS), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO), are rigorously examined. …”
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Human autonomy teaming-based safety-aware navigation through bio-inspired and graph-based algorithms by Timothy Sellers, Tingjun Lei, Chaomin Luo, Zhuming Bi, Gene Eu Jan

“…An integral component of this system is the improved Node Selection Algorithm (iNSA), which utilizes the revised Grey Wolf Optimization (rGWO) for better adaptability and performance. …”
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Advanced control parameter optimization in DC motors and liquid level systems by Serdar Ekinci, Davut Izci, Mohammad H. Almomani, Kashif Saleem, Raed Abu Zitar, Aseel Smerat, Vaclav Snasel, Absalom E. Ezugwu, Laith Abualigah

“…Comparative assessments with competitive algorithms, such as the grey wolf optimizer and particle swarm optimization, reveal MGO’s superior performance. …”
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An Enhanced Comprehensive Learning Particle Swarm Optimizer with the Elite-Based Dominance Scheme by Chengcheng Chen, Xianchang Wang, Helong Yu, Nannan Zhao, Mingjing Wang, Huiling Chen

“…In this paper, the elite-based dominance scheme of another well-established method, grey wolf optimizer (GWO), is introduced into the CLPSO, and the grey wolf local enhanced comprehensive learning PSO algorithm (GCLPSO) is proposed. …”
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Optimal Sizing of Isolated Microgrid Containing Photovoltaic/Photothermal/Wind/Diesel/Battery by Guo Zhao, Tianhua Cao, Yudan Wang, Huirui Zhou, Chi Zhang, Chenxi Wan

“…The three-objective sizing optimization model was solved by the improved multiobjective grey wolf optimization algorithm. …”
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Research on Nonlinear Error Compensation and Intelligent Optimization Method for UAV Target Positioning by Yinglei Li, Qingping Hu, Shiyan Sun, Wenjian Ying, Xiaojia Yan

“…Simulation experiments show that the positioning error distance of the KYCOA is reduced by 66.75%, 41.89%, and 62.06% when compared with that of the original Coati Optimization Algorithm (COA), Grey Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA), respectively. …”
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Optimization of Operation Strategy of Multi-Islanding Microgrid Based on Double-Layer Objective by Zheng Shi, Lu Yan, Yingying Hu, Yao Wang, Wenping Qin, Yan Liang, Haibo Zhao, Yongming Jing, Jiaojiao Deng, Zhi Zhang

“…In this paper, the cooperative operation process of shared energy storage participating in multiple island microgrid systems is researched, and the two-stage research on multi-microgrid operation mode and shared energy storage optimization service cost is focused on. In the first stage, the output of each subject is determined with the goal of profit optimization and optimal energy storage capacity, and the modified grey wolf algorithm is used to solve the problem. …”
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Topology-Aware Anchor Node Selection Optimization for Enhanced DV-Hop Localization in IoT by Haixu Niu, Yonghai Li, Shuaixin Hou, Tianfei Chen, Lijun Sun, Mingyang Gu, Muhammad Irsyad Abdullah

“…However, in practical IoT networks, node distribution is often non-uniform, leading to complex and irregular topologies that significantly reduce the localization accuracy of the original DV-Hop algorithm. To improve localization performance in non-uniform topologies, we propose an enhanced DV-Hop algorithm using Grey Wolf Optimization (GWO). …”
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An ensemble of deep representation learning with metaheuristic optimisation algorithm for critical health monitoring using internet of medical things by Mai Alduailij

“…For the feature selection process, the binary grey wolf optimization (BGWO) model is employed to identify and retain the most significant features in the dataset. …”
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Underwater Acoustic Signal Prediction Based on MVMD and Optimized Kernel Extreme Learning Machine by Hong Yang, Lipeng Gao, Guohui Li

“…Based on the prediction model of kernel extreme learning machine (KELM), this paper uses grey wolf optimization (GWO) algorithm to optimize and select its regularization parameters and kernel parameters and proposes an optimized kernel extreme learning machine OKELM. …”
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Optimized hybrid deep learning for cross-linguistic sentiment analysis: a novel approach by Vipin Jain, Lokesh Malviya, Anjana .S

“…Unlike previous techniques, our model includes the Grey Wolf Optimization (GWO) algorithm for hyperparameter tweaking, which improves both accuracy and efficiency in multilingual sentiment analysis. …”
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An Enhanced Distribution System Performance with Optimization Techniques for Location of Electrical Vehicle Charging Stations by Sainadh Singh Kshatri, Venkata Anjani Kumar G, Chilakapati Lenin Babu, Palepu Suresh Babu

“…The proposed methodology leverages the Grey Wolf Optimization (GWO) metaheuristic algorithm, enthused by the grey wolves hunting, to identify the most strategic locations for EVCSs. …”
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Abnormal Diagnosis Method of Self-Powered Power Supply System Based on Improved GWO-SVM by Ya jie Li, Shao bing Li, Wei Li

“…In order to solve the problem of low abnormal diagnosis rate of self-powered power supply system, an improved grey wolf optimization-support vector machine (GWO-SVM) algorithm combined with maximal information coefficient (MIC) are proposed. …”
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An Actor–Critic-Based Hyper-Heuristic Autonomous Task Planning Algorithm for Supporting Spacecraft Adaptive Space Scientific Exploration by Junwei Zhang, Liangqing Lyu

“…At the bottom level of the hyper-heuristic algorithm, this paper uses the particle swarm optimization algorithm, grey wolf optimization algorithm, differential evolution algorithm, and positive cosine optimization algorithm as the basic operators. …”
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Optimizing Vehicle Placement in the Residual Spaces of Unmarked Parking Areas: A Comparative Study of Heuristic Methods by Mustafa Hüsrevoğlu, Artur Janowski, Ahmet Emin Karkınlı

“…This study investigates the optimal allocation of additional vehicles in spaces left unoccupied around parked cars by comparing seven heuristic optimization algorithms: Particle Swarm Optimization, Artificial Bee Colony, Gray Wolf Optimizer, Harris Hawks Optimizer, Phasor Particle Swarm Optimization, Multi-Population Based Differential Evolution, and the Colony-Based Search Algorithm. …”
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Interpretable prediction model for hand-foot-and-mouth disease incidence based on improved LSTM and XGBoost by Xiao LI, Shuyu HE, Yan PENG, Rongxin YANG, Lu TAO, Tingqi LOU, Wenqi HE

“…In order to address the issues of low accuracy and poor interpretability in existing HFMD incidence prediction models, in this paper, we propose an interpretable prediction model, namely, ARIMA–LSTM–XGBoost, which integrates multiple meteorological factors with Autoregressive integrated moving average model (ARIMA), Long short-term memory (LSTM), Extreme gradient boosting (XGBoost), Grey wolf optimizer (GWO), Genetic algorithm (GA) and Shapley additive explanations (SHAP). …”
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