Research on Fire Detection of Cotton Picker Based on Improved Algorithm by Zhai Shi, Fangwei Wu, Changjie Han, Dongdong Song

“…Therefore, in this study, we designed an improved algorithm for multi-sensor data fusion; built a cotton picker fire detection system by using infrared temperature sensors, CO sensors, and the upper computer; and proposed a BP neural network model based on improved mutation operator hybrid gray wolf optimizer and particle swarm optimization (MGWO-PSO) algorithm based on the BP neural network model. …”
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An improved catastrophe progression method based on HMSLGWO–AHP for grouting quality assessment by Yushan Zhu, Zhu Yang, Ning Li, Jian Huang

“…Subsequently, the analytic hierarchy process (AHP) method improved by the hierarchical multi‐strategy learning gray wolf optimization (HMSLGWO) algorithm is employed to determine the relative significance of indices, in which, the HMSLGWO algorithm, augmented by Gaussian mixture model clustering and multi‐strategy learning, optimizes the consistency of the AHP judgment matrix. …”
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Multi-Parameter Optimization Using Metaheuristic Algorithms to Improve Uncrewed Aerial Vehicles’ Wireless Communications: A Performance Analysis by Lalan J. Mishra, Naima Kaabouch

“…In Approach 2, particle swarm optimization converged fastest, while gray wolf optimization was slowest. …”
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Energy efficient adaptive clustering with QoS-aware CBRP and grey wolf optimization clustering algorithm for mobile ad-hoc network (MANET) by Minal Patil, Manish Chawhan, Roshan Umate, Abhishek Madankar, Bhumika Neole

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Link and Loss Aware GW-COOP Routing Protocol for FANETs by Shahzad Hameed, Saleh Alyahya, Qurratul-Ain Minhas, Shabana Habib, Asif Nawaz, Sheeraz Ahmed, Atif Ishtiaq, Muhammad Islam, Sheroz Khan

“…This paper proposes GW-COOP (Gray Wolf Algorithm using Cooperative Diversity Technique) routing protocol for FANETs. …”
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Hybrid Gradient Descent Grey Wolf Optimizer for Machine Learning Performance Enhancement by Sri Rossa Aisyah Puteri Baharie, Sugiyarto Surono, Aris Thobirin

“…Advancements in machine learning have enabled the development of more accurate and efficient health prediction models. This study aims to improve diabetes prediction performance using the Support Vector Machine (SVM) model optimized with the Hybrid Gradient Descent Gray Wolf Optimizer (HGD-GWO) method. …”
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Optimization of rotor-side controller parameters in doubly fed induction generators based on an improved NSGA-II. by Yanling Lv, Xiang Zhao, Zexin Mou

“…Comparative simulations using the traditional NSGA-II, a multiobjective particle swarm optimization algorithm, and a multiobjective gray wolf optimization algorithm are conducted to validate the proposed algorithm. …”
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A multi-objective improved horse herd optimizer based on convex lens imaging for stochastic optimization of wind energy resources in distribution networks considering reliability a... by Fude Duan, Ali Basem, Dheyaa J. Jasim, Mahdiyeh Eslami, Mustafa Okati

“…Moreover, the superiority of the MOIHHO is investigated in achieving better objective function value compared with conventional MOHHO, multi-objective particle swarm optimization (MOSPO), multi-objective gray wolf optimizer (MOGWO), and multi-objective gazelle optimization algorithm (MOGOA). …”
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Extraction of the Optimal Parameters of Single-Diode Photovoltaic Cells Using the Earthworm Optimization Algorithm by Fatima Wardi, Mohamed Louzazni, Mohamed Hanine

“…Furthermore, the outcomes obtained via the EOA are contrasted with those derived from other algorithms, namely gray wolf optimizer (GWO), whale optimization algorithm (WOA), sine cosine algorithm (SCA), moth–flame optimization (MFO), ant lion optimizer (ALO), and multiverse optimizer (MVO). …”
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Prediction of surface deformation time series in closed mines based on LSTM and optimization algorithms by Hu Caixiong, Zhang Lili, Li Haoran, Zhang Yaowen, Yao Yunsheng

“…A long short-term memory (LSTM) neural network combined with the gray wolf optimizer (GWO) algorithm was introduced to improve prediction accuracy. …”
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Three-Dimensional Path Planning for Unmanned Aerial Vehicles Based on Hybrid Multi-Strategy Dung Beetle Optimization Algorithm by Hongmei Fei, Ruru Liu, Leilei Dong, Zhaohui Du, Xuening Liu, Tao Luo, Jie Zhou

“…To validate the effectiveness of HMSDBO, this study compares its performance with that of the Adaptive Chaotic Gray Wolf Optimization Algorithm (ACGWO), Primitive Dung Beetle Optimization Algorithm (DBO), Whale Optimization Algorithm (WOA), Crayfish Optimization Algorithm (COA), and Hyper-Heuristic Whale Optimization Algorithm (HHWOA) in complex agricultural UAV environments. …”
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Optimization of Fuzzy Adaptive Logic Controller for Robot Manipulators Using Modified Greater Cane Rat Algorithm by Jian Sun, Shuyi Wu, Jinfu Chen, Xingjia Li, Ziyan Wu, Ruiting Xia, Wei Pan, Yan Zhang

“…For benchmarking, several state-of-the-art swarm intelligence algorithms—including particle swarm optimization (PSO), artificial bee colony (ABC), ant colony optimization (ACO), gray wolf optimization (GWO), covariance matrix adaptation evolution strategy (CMA-ES), adaptive guided differential evolution (AGDE), the basic greater cane rat algorithm (GCRA), and a trial-and-error method—are compared under identical conditions. …”
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Enhanced Prediction and Evaluation of Hydraulic Concrete Compressive Strength Using Multiple Soft Computing and Metaheuristic Optimization Algorithms by Tianyu Li, Xiamin Hu, Tao Li, Jie Liao, Lidan Mei, Huiwen Tian, Jinlong Gu

“…In the initial stage, several classic machine learning models are selected as base models, and the optimal parameters of these models are obtained using the improved metaheuristic-based gray wolf algorithm. …”
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Enhanced Automatic Generation Control in Multiarea Power Systems: Crow Search Optimized Cascade FOPI‐TIDDN Controller With Integrated Renewable Solar Thermal Models and HVDC Lines... by Naladi Ram Babu, Pamarthi Sunitha, Ganesh Pardhu B. S. S., Sanjeev Kumar Bhagat, Adireddy Ramesh, Arindita Saha, Wulfran Fendzi Mbasso, Pradeep Jangir, Ahmed Hossam‐Eldin

“…ABSTRACT As renewable energy sources (RES) are increasingly unified into multiarea power systems, automatic generation control (AGC) faces challenges such as frequency instability, longer settling times, and higher overshoot. While existing optimization techniques like Firefly (FF) and gray wolf (GW) suffer from slow convergence and local optima trapping, conventional controllers like FOPI, PIDN, TIDN, and TIDDN struggle to maintain stability under fluctuating load conditions. …”
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Orthogonal Multi‐Swarm Greedy Selection Based Sine Cosine Algorithm for Optimal FACTS Placement in Uncertain Wind Integrated Scenario Based Power Systems by Sunilkumar P. Agrawal, Pradeep Jangir, Arpita, Sundaram B. Pandya, Anil Parmar, Mohammad Khishe, Bhargavi Indrajit Trivedi

“…Flexible AC Transmission System (FACTS) devices, including Static VAR Compensator (SVC), Thyristor‐Controlled Series Compensator (TCSC), and Thyristor‐Controlled Phase Shifter (TCPS), enhance system stability, reduce losses, and lower operational costs when optimally placed. Conventional optimization techniques like Particle Swarm Optimization (PSO), Sine Cosine Algorithm (SCA), Moth Flame Optimization (MFO), Gray Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA) struggle to balance exploration and exploitation in complex OPF problems, leading to suboptimal solutions. …”
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An efficient approach for mathematical modeling and parameter estimation of PEM fuel based on Young’s double-slit experiment algorithm by Basma S. Alqadi, Deema Mohammed Alsekait, Mohamed F. Issa, Essam H. Houssein, Fatma H. Ismail, Mokhtar Said, Nour Mostafa, Fahmi Elsayed

“…The proposed method integrates the YDSE algorithm with five other metaheuristic techniques: the sine cosine Algorithm (SCA), moth flame optimization (MFO), Harris Hawk optimization (HHO), gray wolf optimization (GWO) and chimp optimization Algorithm (ChOA) to estimate six critical parameters of PEMFC. …”
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Optimizing Route Planning via the Weighted Sum Method and Multi-Criteria Decision-Making by Guanquan Zhu, Minyi Ye, Xinqi Yu, Junhao Liu, Mingju Wang, Zihang Luo, Haomin Liang, Yubin Zhong

“…Secondly, this study compares seven heuristic algorithms—the genetic algorithm (GA), particle swarm optimization (PSO), the tabu search (TS), genetic-particle swarm optimization (GA-PSO), the gray wolf optimizer (GWO), and ant colony optimization (ACO)—to solve the TOPSIS model, with GA-PSO performing the best. …”
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Optimum Design of a Photovoltaic Inverter System Based on Ga, Pso and Gwo Algorithms with a Mppt Sliding Mode Control by Alberto Coronado-Mendoza, Mónica Camas-Náfate, Jesús Sergio Artal-Sevil, José Antonio Domínguez-Navarro

“…Furthermore, eight system parameters are optimized using advanced techniques such as genetic algorithms, particle swarm optimization, and gray wolf optimization. …”
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Smart homes energy management: Optimal multi-objective appliance scheduling model considering electrical energy storage and renewable energy resources by Moslem Dehghani, Seyyed Mohammad Bornapour

“…The maximum standard deviation of total objective function between all cases for IBBO, gray wolf optimizer (GWO), and whale optimization algorithm (WOA) are 6.55, 17.22, and 24.87, respectively, which show the robustness of IBBO in finding the best solution in comparisons of other algorithms. …”
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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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