Bearing Fault Prediction Based on Mixed Domain Features and GWO-SVM by Xuan Zhou, Ruiyang Xia, Zhaodong Zhang, Sasa Duan, Mao Cheng, Chengjiang Zhou, Min Mao

“…We propose a bearing fault identification algorithm based on grey wolf optimizer (GWO) to address the common problems of high signal noise, inability of a single indicator to accurately reflect the true state of bearings, and optimization of support vector machine (SVM) prediction model parameters in bearing fault identification. …”
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A Decomposition-Integration Framework of Carbon Price Forecasting Based on Econometrics and Machine Learning Methods by Zhehao Huang, Benhuan Nie, Yuqiao Lan, Changhong Zhang

“…The framework subsequently employs GARCH models for predicting high-frequency components and a gated recurrent unit (GRU) neural network optimized by the grey wolf algorithm for low-frequency components. …”
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Neural network prediction model based on Levy flight and natural biomimetic technology for its application in cancer prediction. by Ruiyu Zhan

“…To tackle this issue, we present an innovative method that harmonizes the Grey Wolf Optimizer (GWO) with Levy flight to optimize the weights and biases of a Backpropagation (BP) neural network-a prominent machine learning model extensively employed in classification tasks. …”
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Data-driven framework for prediction of mechanical properties of waste glass aggregates concrete by Kennedy C. Onyelowe, Shadi Hanandeh, Viroon Kamchoom, Ahmed M. Ebid, Hamza Imran, Miguel Angel Duque Vaca, Greys Carolina Herrera Morales, Nestor Ulloa, Krishna Prakash Arunachalam

“…Abstract This research presents a novel data-driven framework for predicting the mechanical properties of waste glass aggregate concrete using six advanced metaheuristic optimization algorithms: Bat Algorithm (Bat), Cuckoo Search Algorithm (Cuckoo), Elephant Herding Optimization (Elephant), Firefly Algorithm (Firefly), Rhinoceros Optimization Algorithm (Rhino), and Gray Wolf Optimizer (Wolf). …”
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ARIMA-Kriging and GWO-BiLSTM Multi-Model Coupling in Greenhouse Temperature Prediction by Wei Zhou, Shuo Liu, Junxian Guo, Na Liu, Zhenglin Li, Chang Xie

“…Utilizing the high-quality data processed by this model, this study proposes and constructs a novel Grey Wolf Optimizer and Bidirectional Long Short-Term Memory (GWO-BiLSTM) temperature prediction framework, which combines a Grey Wolf Optimizer (GWO)-enhanced algorithm with a Bidirectional Long Short-Term Memory (BiLSTM) network. …”
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Research on Power Conversion and Control Technology of Ocean Buoy Tidal Energy Power Supply System by Changpo Song, Fengyong Sun, Fan Yang

“…This paper proposes a Boost + LLC converter-based power controller for ocean buoy tidal energy systems. To optimize output power across a wide input voltage range (40–120 V) and achieve effective power tracking control, we introduce two key innovations as follows: (1) a variable-mode inverter hybrid control strategy, combining smooth-mode switching with inverter control to enable wide gain range regulation. (2) An improved Grey Wolf Optimization (GWO) algorithm, enhanced by integrating a PSO-based elite wolf search strategy preventing local optima and maximizing power capture. …”
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A smarter approach to liquefaction risk: harnessing dynamic cone penetration test data and machine learning for safer infrastructure by Shubhendu Vikram Singh, Sufyan Ghani

“…ML models, including Support Vector Machine (SVM) optimized with Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Genetic Algorithm (GA), and Firefly Algorithm (FA), were employed to predict the e/qd ratio using key geotechnical parameters, such as fine content, peak ground acceleration, reduction factor, and penetration rate. …”
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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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RESEARCH OF EARLY FAULT FEATURE EXTRACTION OF SOLAR WHEEL BASED ON PARAMETRIC ADAPTIVE ICEEMDAN AND MCKD by ZHAO Naizhuo, ZHAO Yumeng, MEN Chengfu

“…In order to solve the problem of difficult to accurately extract early faults of solar wheels under the strong noise background, an improved grey wolf algorithm (newGWO) was proposed to optimize and improve the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and the maximum correlated kurtosis deconvolution (MCKD) for early fault feature extraction of solar wheels.NewGWO was used to optimize the selection of parameters of the white noise amplitude weight and noise addition times that affected the decomposition effect.The fault vibration signal was decomposed by newGWO-ICEEMDAN, and the minimum envelope entropy was selected as the fitness function to obtain several related modal components.Then, the envelope spectrum peak factor was selected as the best modal component index.MCKD signals optimized by newGWO were enhanced for the selected optimal intrinsic mode function （IMF） components. …”
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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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A Study of the Soil–Wall–Indoor Air Thermal Environment in a Solar Greenhouse by Zhi Zhang, Yu Li, Liqiang Wang, Weiwei Cheng, Zhonghua Liu

“…The temperature change can be classified into four categories according to K-means classification, which was optimized based on the grey wolf algorithm. The categories were as follows: high-temperature region, medium-high temperature region, medium-low temperature region, and low-temperature region. …”
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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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Application of Improved LSTM Model in Runoff Simulation in Arid Region of Northwest China: A Case Study of the Zuli River by SONG Haiping, TANG Yiran, DANG Wentao, WANG Yibo

“…Using observed runoff, precipitation, and monthly mean temperature data from 1980 to 2020, the research incorporated feature engineering, combined with extreme-value post-processing and mixed loss function optimization. On this basis, the grey wolf optimization (GWO) algorithm was used to optimize the parameters of the LSTM-Attention model, and the GWO-LSTM-Attention model was constructed, enhancing the models' capability to capture the region's complex runoff mechanisms. …”
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Microgrid system for electric vehicle charging stations integrated with renewable energy sources using a hybrid DOA–SBNN approach by Kommoju Naga Durga Veera Sai Eswar, M. Arun Noyal Doss, Mohammad Shorfuzzaman, Ali Elrashidi

“…The proposed method outperforms all current techniques, including the Multi swarm Optimization (MSO), the Multi-Objective Gray Wolf Optimizer (MOGWO), and the Modified Multi-objective Salp Swarm Optimization algorithm (MMOSSA). …”
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A strategic approach to the placement of PV-integrated EV charging stations for enhancing the distribution network performance by Raj Chakraborty, Subhojit Dawn, Priyanath Das, Diptanu Das, Sadhan Gope, Md. Minarul Islam, Taha Selim Ustun

“…The outcomes have been compared with Grey Wolf Optimizer, particle swarm optimization (PSO), and whale optimization algorithm (WOA) to validate the effectiveness of the optimal planning to allocate the EVCS and PV units. …”
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Development and application of advanced learning models for predicting the land subsidence due to coal mining by Shirin Jahanmiri, Majid Noorian-Bidgoli

“…Three hybrid models—biogeography-based optimization with gene expression programming (BBO-GEP), gray wolf optimizer with gene expression programming (GWO-GEP), and salp swarm algorithm with gene expression programming (SSA-GEP)—are applied to assess subsidence risks. …”
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Bio-inspired clustering scheme for Internet of Drones application in industrial wireless sensor network by Farooq Aftab, Ali Khan, Zhongshan Zhang

“…The results indicate that the proposed scheme has improved 60% and 38% with respect to ant colony optimization and grey wolf optimization, respectively, in terms of average cluster building time while average energy consumption has improved 23% and 33% when compared to the ant colony optimization and grey wolf optimization, respectively.…”
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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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PV Based Standalone DC -Micro Grid System for EV Charging Station with New GWO-ANFIS MPPTs under Partial Shading Conditions by R. Ragul, N. Shanmugasundaram, Mariaraja Paramasivam, Suresh Seetharaman, Sheela L. Mary Immaculate

“…The second issue called they are unable to track the new GMPPs after it has changed positions is addressed in this work by using novel initialization by GWOs (Grey wolf Optimizations). In the MATLAB-Simulink and experiments demonstrate the effectiveness of the suggested GWO-ANFIS MPPTs based off-grid station for EVs (Electrical Vehicle) battery charging.…”
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Cost-benefit analysis in demand response with penalty and grid management using blockchain by Manikandan Ramasamy, Thenmalar Kaliannan, Saravanakumar Ramasamy

“…Two distinct optimization methods such as the gray wolf optimization algorithm and particle swarm optimization are employed to solve the optimization model. …”
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