Design of Nonlinear PID and FOPID Controllers for Electronic Throttle Valve Plate’s Position by Mohamed Jasim Mohamed, Luay Thamir Rasheed

“…However, all these control schemes above have been studied with and without considering the technique of manipulating the windup problem or antiwindup. A metaheuristic optimization technique, namely, the grey wolf optimization (GWO) algorithm, is introduced for optimizing the controllers’ parameters while minimizing the integral of the cube time square error (IT^3SE) cost function. …”
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Machine learning approach for prediction of safe mud window based on geochemical drilling log data by Hongchen Cai, Yunliang Yu, Yingchun Liu, Xiangwei Gao

“…Traditional geomechanical methods for SMW determination face challenges in handling complex, nonlinear relationships within drilling datasets.PurposeThis study aims to develop robust machine learning (ML) models to predict two key SMW parameters—Mud Pressure below shear failure (MWsf) and tensile failure (MWtf)—using geochemical drilling log data from Middle Eastern carbonate reservoirs.MethodsHybrid ML models combining Least Squares Support Vector Machine (LSSVM) and Multilayer Perceptron (MLP) with optimization algorithms (Gray Wolf Optimization, GWO; Grasshopper Optimization Algorithm, GOA) were trained on 2,820 data points from three wells. …”
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Conceptual Approach to Permanent Magnet Synchronous Motor Turn-to-Turn Short Circuit and Uniform Demagnetization Fault Diagnosis by Yinquan Yu, Chun Yuan, Dequan Zeng, Giuseppe Carbone, Yiming Hu, Jinwen Yang

“…Firstly, analyzing the PMSM turn-to-turn short-circuit and demagnetization faults, one takes the PMSM stator current as the fault signal and optimizes the variational modal decomposition (VMD) by using the Gray Wolf Optimization (GWO) algorithm in order to achieve efficient noise reduction processing of the stator current signal and improve the fault feature content in the stator current signal. …”
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Device-Driven Service Allocation in Mobile Edge Computing with Location Prediction by Qian Zeng, Xiaobo Li, Yixuan Chen, Minghao Yang, Xingbang Liu, Yuetian Liu, Shiwei Xiu

“…We also design an improved service allocation strategy, MESDA, based on the Gray Wolf Optimization (GWO) algorithm. MESDA dynamically adjusts its exploration and exploitation components, and introduces a random factor to enhance the algorithm’s ability to determine the direction during later stages. …”
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Comparative techno-economic analysis of grid-connected solar PV-battery and PV-fuel cell systems for educational institutions sustainable academic laboratories by Takele Ferede Agajie, Fuseini Seidu Ibrahim, Isaac Amoussou, Elsabet Ferede Agajie, Eriisa Yiga Paddy, Yayehyirad Ayalew Awoke, Wirnkar Basil Nsanyuy, Mohit Bajaj

“…Three algorithms were used: Teaching–Learning-Based Optimization (TLBO), Water Cycle Algorithm (WCA), and Improved Grey Wolf Optimization (I-GWO). …”
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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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Effect of Voltage Dependent Load Model on Placement and Sizing of Distributed Generator in Large Scale Distribution System by Gopisetti Manikanta, Ashish Mani, Hemender Pal Singh, Devendra Kumar Chaturvedi

“…In addition to AQiEA, four other algorithms (Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Grey Wolf Optimization (GWO), and Ecogeography-based Optimization (EBO) with Classification based on Multiple Association Rules (CMAR)) have also been employed for comparison. …”
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An intelligent fault diagnosis model for bearings with adaptive hyperparameter tuning in multi-condition and limited sample scenarios by Jianqiao Li, Zhihao Huang, Liang Jiang, Yonghong Zhang

“…To address these issues, this paper presents an advanced diagnosis method using a hybrid Grey Wolf Algorithm (HGWA)-optimized convolutional neural network (CNN) and Bidirectional long short-term memory (BiLSTM) architecture. …”
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Study on vibration characteristic of battery pack of electric excavator under non-stationary random excitation by LI Zhaojun, LI Feibiao, WANG Bo, ZHAO Ming, WU Fangming

“…The research shows that reconstructing road excitation signals based on wavelet transform and Grey Wolf Optimization-Variational Mode Decomposition (GWO-VMD) signal analysis algorithm can effectively reflect the characteristics of road excitation. …”
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Fault Diagnosis of Rolling-Element Bearing Using Multiscale Pattern Gradient Spectrum Entropy Coupled with Laplacian Score by Xiaoan Yan, Ying Liu, Peng Ding, Minping Jia

“…To address this problem, a novel approach entitled multiscale pattern gradient spectrum entropy (MPGSE) is further implemented to extract fault features across multiple scales, where its key parameters are determined adaptively by grey wolf optimization (GWO). Meanwhile, a Laplacian score- (LS-) based feature selection strategy is employed to choose the sensitive features and establish a new feature set. …”
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Using SVM Classifier and Micro-Doppler Signature for Automatic Recognition of Sonar Targets by Abbas Saffari, Seyed Hamid Zahiri, Navid Khozein Ghanad

“…For a more fair comparison, multilayer perceptron neural network with two back-propagation (MLP-BP) training methods and gray wolf optimization (MLP-GWO) algorithm were used. …”
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Task Allocation and Path Planning Method for Unmanned Underwater Vehicles by Feng Liu, Wei Xu, Zhiwen Feng, Changdong Yu, Xiao Liang, Qun Su, Jian Gao

“…First, we introduce a task allocation mechanism based on an Improved Grey Wolf Algorithm (IGWA). This mechanism comprehensively considers factors such as target value, distance, and UUV capability constraints to achieve efficient and reasonable task allocation among UUVs. …”
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Numerical Prediction of Solid Particle Erosion in Jet Pumps Based on a Calibrated Model by Xuanchen Wan, Mengxue Dong, Maosen Xu, Chuanhao Fan, Jiegang Mou, Shuai Han

“…The CFD-DEM method was used to simulate the solid–liquid two-phase flow in the jet pump, comparing six erosion models for predicting erosion rates. The Grey Wolf Optimization algorithm was applied to calibrate model coefficients. …”
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A Study on Hyperspectral Soil Moisture Content Prediction by Incorporating a Hybrid Neural Network into Stacking Ensemble Learning by Yuzhu Yang, Hongda Li, Miao Sun, Xingyu Liu, Liying Cao

“…First, raw hyperspectral data are processed by removing edge noise and standardization. Then, the gray wolf optimization (GWO) algorithm is adopted to optimize a convolutional neural network (CNN), and a gated recurrent unit (GRU) and an attention mechanism are added to construct a hybrid neural network model (GWO–CNN–GRU–Attention). …”
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Improving Vehicle Dynamics: A Fractional-Order PI<i>^λ</i>D<i>^μ</i> Control Approach to Active Suspension Systems by Zongjun Yin, Chenyang Cui, Ru Wang, Rong Su, Xuegang Ma

“…A fractional-order PI<i>^λ</i>D<i>^μ</i> (FOPID) controller was proposed, and its structural parameters were optimized using a gray wolf optimization algorithm. …”
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Research on subway settlement prediction based on the WTD-PSR combination and GSM-SVR model by Miren Rong, Chao Feng, Yinping Pang, Hailong Wang, Ying Yuan, Wensong Zhang, Lanxin Luo

“…Furthermore, Particle Swarm Optimization (PSO), Gray Wolf Optimization (GWO), Marine Predators Algorithm (MPA), and Whale Optimization Algorithm (WOA) are introduced to optimize the SVR model, and the prediction performance is compared with that of the Long Short-Term Memory (LSTM) model. …”
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Research on productivity prediction method of infilling well based on improved LSTM neural network: A case study of the middle-deep shale gas in South Sichuan by GUAN Wenjie, PENG Xiaolong, ZHU Suyang, YANG Chen, PENG Zhen, MA Xiaoran

“…In order to quickly and accurately predict the production capacity of infilling wells, this study classifies the “three-stage” declining trend observed in the production pressure curves of existing wells into: (1) A drastic decline period, regarded as the initial water production stage; (2) a rapid decline period; and (3) a slow decline period, both considered part of the later gas production stage. The Grey Wolf Optimizer(GWO) algorithm, a fast optimization algorithm with adaptive capabilities and an information feedback mechanism, is applied for hyperparameter optimization of the Long Short-term Memory (LSTM) neural network. …”
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Security Enhancement of Power Systems through Interline Power Flow Controller (IPFC) under Contingency Condition: A Case Study and Analysis‐EEP 400 kV System by Muluneh Lemma Woldesemayat, Ashenafi Tesfaye Tantu

“…In this research, the optimal sizing of IPFC was done by using Grey Wolf Optimization (GWO) algorithm. …”
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Detection of false data injection in electric energy metering platforms using gradient lifting decision trees and MLP neural networks by Yakui Zhu, Yangrui Zhang, Chao Zhang, Bingyu Zhang, Hongying Wang, Shaokang Feng

“…The improved Cauchy mutation grey Wolf optimization algorithm is used to optimize the model training to improve the detection accuracy. …”
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Prediction of river dissolved oxygen (DO) based on multi-source data and various machine learning coupling models. by Yubo Zhao, Mo Chen

“…In this study, a hybrid machine learning model for river DO prediction, called DWT-KPCA-GWO-XGBoost, is proposed, which combines the discrete wavelet transform (DWT), kernel principal component analysis (KPCA), gray wolf optimization algorithm (GWO), and extreme gradient boosting (XGBoost). …”
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