A Systematic Mapping Study on State Estimation Techniques for Lithium-Ion Batteries in Electric Vehicles by Carolina Tripp-Barba, José Alfonso Aguilar-Calderón, Luis Urquiza-Aguiar, Aníbal Zaldívar-Colado, Alan Ramírez-Noriega

“…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 optimization frameworks that combine Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO). …”
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Advanced time-series InSAR analysis to estimate surface deformation and utilization of hybrid deep learning for susceptibility mapping in the Jakarta metropolitan region by Wahyu Luqmanul Hakim, Muhammad Fulki Fadhillah, Joong-Sun Won, Yu-Chul Park, Chang-Wook Lee

“…The metaheuristic algorithms are the gray wolf optimizer (GWO) and the imperialist competitive algorithm (ICA). …”
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MAPE-ViT: multimodal scene understanding with novel wavelet-augmented Vision Transformer by Muhammad Waqas Ahmed, Touseef Sadiq, Hameedur Rahman, Sulaiman Abdullah Alateyah, Mohammed Alnusayri, Mohammed Alatiyyah, Dina Abdulaziz AlHammadi

“…The feature discrimination capability is further enhanced through optimization using the Gray Wolf algorithm. The processed features then flow into a dual-stream architecture, where an extreme learning machine handles multi-object classification, while conditional random fields (CRF) manage scene-level categorization. …”
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Minimizing Power Consumption and Interference Mitigation of Downlink NOMA HetNets by IRS-Supported Aerial Base Stations by Osamah Thamer Hassan Alzubaidi, Mhd Nour Hindia, Kaharudin Dimyati, Kamarul Ariffin Noordin, Faizan Qamar, Atef Abdrabou

“…To tackle this problem, a meta-heuristic algorithm based on the modified gray wolf optimization (MGWO) and an alternation max/min technique based on the developed Block Coordinate Descent (DBCD) are proposed. …”
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Task Allocation and Saturation Attack Approach for Unmanned Underwater Vehicles by Qiangqiang Chen, Baisheng Liu, Changdong Yu, Mingkai Yang, Haonan Guo

“…In the task allocation link, the grey wolf optimizer is improved by introducing Logistic chaos mapping and differential evolution mechanism, which improves the search efficiency and allocation accuracy. …”
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Dual-hybrid intrusion detection system to detect False Data Injection in smart grids. by Saad Hammood Mohammed, Mandeep S Jit Singh, Abdulmajeed Al-Jumaily, Mohammad Tariqul Islam, Md Shabiul Islam, Abdulmajeed M Alenezi, Mohamed S Soliman

“…The proposed methodology combines Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) for hybrid feature selection, ensuring the selection of the most relevant features for detecting FDIAs. …”
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Machine learning-driven design of rare metal doped niobium alloys with enhanced strength and ductility by Zhenqiang Xiong, Zhaokun Song, Jianwei Li, Heran Wang, Xiaoxin Zhang, Bin Liang, Dong Wang

“…A comprehensive database of niobium alloys' properties was analyzed using feature engineering, and a high-accuracy prediction model, Gray Wolf Optimization-Extreme Learning Machine (GWO-ELM), was constructed, achieving R2 values of 0.95 and 0.88 for tensile strength and elongation, respectively. …”
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A novel Hadamard matrix based hybrid compressive sensing technique for enhancing energy efficiency and network longevity by Balamurali S, Kathirvelu M, SatheeshKumar Palanisamy, Tagrid Abdullah N. Alshalali

“…By adopting improved versions of Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and novel Hadamard matrix-based hybrid compressed sensing techniques, NHM-HCS enhances the network’s lifespan and improves other performance metrics. …”
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A novel voting ensemble model empowered by metaheuristic feature selection for accurate flash flood susceptibility mapping by Radhwan A. Saleh, Ahmed M. Al-Areeq, Amran A. Al Aghbari, Mustafa Ghaleb, Mohammed Benaafi, Nabil M. Al‑Areeq, Baqer M. Al-Ramadan

“…Through comprehensive comparisons with established algorithms such as the Artificial Bee Colony (ABC) and Gray Wolf Optimizer (GWO), MSA refined the selection, identifying 'elevation’ and 'distance to streams’ as optimal factors. …”
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A data-driven state identification method for intelligent control of the joint station export system by Guangli Xu, Yifu Wang, Zhihao Zhou, Yifeng Lu, Liangxue Cai

“…In this paper, a combination of Particle Swarm Optimization (PSO) and Gray Wolf Optimizer (GWO) is proposed to optimize the Backpropagation Neural Network (BP) model (PSO-GWO-BP) and a pressure drop prediction model for the joint station export system is established using PSO-GWO-BP. …”
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Numerical analysis method of stress wave transmission attenuation of coal and rock structural plane by Wenlong SHEN, Renren ZHU, Ziqiang CHEN, Guocang SHI

“…The simulation and machine learning of stress wave transmission in the experimental process of Split Hopkinson Pressure Bar (SHPB) were carried out by combining the Barton-Bandis nodal ontology model, UDEC discrete element simulation and Gray Wolf Algorithm optimized BP neural network technology. …”
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Machine learning for defect condition rating of wall wooden columns in ancient buildings by Yufeng Li, Wu Ouyang, Zhenbo Xin, Houjiang Zhang, Shuqi Sun, Dian Zhang, Wenbo Zhang

“…The RBF neural network model achieved the highest accuracy (94.57 %) on the feature fusion dataset, while Grey Wolf Optimizer (GWO) optimization further improved accuracy to 96.74 %. …”
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Ensemble Machine Learning Model Prediction and Metaheuristic Optimisation of Oil Spills Using Organic Absorbents: Supporting Sustainable Maritime by Le Quang Dung, Pham Duc, Bui Thi Anh Em, Nguyen Lan Huong, Nguyen Phuoc Quy Phong, Dang Thanh Nam

“…Operating conditions were optimised using Grey Wolf Optimisation (GWO), showing an optimal percentage of oil removed (POR) of 93.59%. …”
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