Triple-Stream Deep Feature Selection with Metaheuristic Optimization and Machine Learning for Multi-Stage Hypertensive Retinopathy Diagnosis by Süleyman Burçin Şüyun, Mustafa Yurdakul, Şakir Taşdemir, Serkan Biliş

“…In the third stage, feature selection was performed using metaheuristic optimization techniques including Genetic Algorithm (GA), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), and Harris Hawk Optimization (HHO). …”
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An integration of ensemble deep learning with hybrid optimization approaches for effective underwater object detection and classification model by G. Abirami, S. Nagadevi, J. D. Dorathi Jayaseeli, T. Prabhakara Rao, R S M Lakshmi Patibandla, Rajanikanth Aluvalu, K Srihari

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Intelligent optimization method of fracturing parameters for shale oil reservoirs in Jimsar Sag, Junggar Basin, NW China by Yunjin WANG, Fujian ZHOU, Hang SU, Leyi ZHENG, Minghui LI, Fuwei YU, Yuan LI, Tianbo LIANG

“…A policy gradient-genetic-particle swarm algorithm is designed, which can adaptively adjust the inertia weights and learning factors in the iterative process, significantly improving the optimization ability of the optimization strategy. …”
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A Novel Vibration Suppression Method for Welding Robots Based on Welding Pool Instability Evaluation and Trajectory Optimization by Mingtian Ma, Hong Lu, Yongquan Zhang, Zidong Wu, He Huang, Xujie Yuan, Xu Feng, Zhi Liu, Zhangjie Li

“…To enhance the performance of the method, the Particle Swarm Optimization (PSO) algorithm is applied to optimize the joint angular velocity and angular acceleration. …”
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Intelligent Classification Method for Rail Defects in Magnetic Flux Leakage Testing Based on Feature Selection and Parameter Optimization by Kailun Ji, Ping Wang, Yinliang Jia

“…This study addresses the critical challenge of insufficient classification accuracy for different defect signals in rail magnetic flux leakage (MFL) detection by proposing an enhanced intelligent classification framework based on particle swarm optimized radial basis function neural network (PSO-RBF). …”
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Optimizing energy cost in the residential sector through home energy management systems in a smart grid environment by Nabeeha Qayyum, Umar Jamil, Anzar Mahmood

“…A genetic algorithm (GA) based optimization technique was employed to evaluate the performance of a HEMS and validated with particle swarm optimization (PSO) technique under identical initial conditions for each appliance and their corresponding energy pricing over different periods. …”
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Low-carbon and economic optimization of a source-load-storage system based on Stackelberg game and chance constraints by Xu Ke, Liu Chang, Xu Weiting, Zeng Jian, Shao Fan

“…Finally, the model is solved using an improved particle swarm algorithm combined with the Gurobi optimization tool. …”
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SADASNet: A Selective and Adaptive Deep Architecture Search Network with Hyperparameter Optimization for Robust Skin Cancer Classification by Günay İlker, İnik Özkan

“…This method, designated as the SADASNet (Selective and Adaptive Deep Architecture Search Network by Hyperparameter Optimization) algorithm, is developed based on the Particle Swarm Optimization (PSO) technique. …”
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Application of Metaheuristics for Optimizing Predictive Models in iHealth: A Case Study on Hypotension Prediction in Dialysis Patients by Felipe Cisternas-Caneo, María Santamera-Lastras, José Barrera-Garcia, Broderick Crawford, Ricardo Soto, Cristóbal Brante-Aguilera, Alberto Garcés-Jiménez, Diego Rodriguez-Puyol, José Manuel Gómez-Pulido

“…Dialysis session data from 758 patients collected between January 2016 and October 2019 were analyzed. Particle Swarm Optimization, Grey Wolf Optimizer, Pendulum Search Algorithm, and Whale Optimization Algorithm were employed to reduce the feature space, removing approximately 45% of clinical and analytical variables while maintaining high recall for the minority class of patients experiencing hypotension. …”
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Magnetic Actuation for Wireless Capsule Endoscopy in a Large Workspace Using a Mobile-Coil System by Xiao Li, Detian Zeng, Han Xu, Qi Zhang, Bin Liao

“…In particular, the proportional–integral–derivative (PID) control parameters and current values are optimized online and in real time using the adaptive particle swarm optimization (APSO) algorithm. …”
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Robust Optimal Control for a Microbial Batch Culture Processes: Incorporating Free Terminal Time and Sensitivity Analysis by Yang Qi, Zheng Shijin, Xie Suzhen, Feng Enmin

“…Subsequently, we develop an improved particle swarm optimization algorithm to solve this equivalent problem. …”
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Configuration Design and Size Optimization of a High-Precision Novel Parallel Pointing Mechanism Based on Interference Separation by Sen Wang, Shihua Li, Xueyan Han, Jiahao Wei, Xueyuan Gao, Hongyu Xu

“…Finally, in order to find the optimal solution for the workspace and interference force compensation coefficient of the pointing mechanism, multi-objective optimization design of the structural parameters of the mechanism was carried out based on the particle swarm optimization algorithm. …”
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A Data-Driven Method for Predicting and Optimizing Industrial Robot Energy Consumption Under Unknown Load Conditions by Qing Chang, Tiantian Yuan, Haifeng Li, Yuxiang Chen, Xuehao Wang, Sen Gao, Hongsheng Ren, Xiangyun Zhao, Lingyu Wang

“…This paper presents a KAN-LSTM model designed to accurately predict energy consumption under unknown load conditions, alongside a particle swarm optimization (PSO) algorithm for minimizing energy use. …”
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Determination of Sequential Well Placements Using a Multi-Modal Convolutional Neural Network Integrated with Evolutionary Optimization by Seoyoon Kwon, Minsoo Ji, Min Kim, Juliana Y. Leung, Baehyun Min

“…This study proposes a hybrid workflow for determining the locations of production wells during primary oil recovery using a multi-modal convolutional neural network (M-CNN) integrated with an evolutionary optimization algorithm. The particle swarm optimization algorithm provides the M-CNN with full-physics reservoir simulation results as learning data correlating an arbitrary well location and its cumulative oil production. …”
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Aero Engine Component Fault Diagnosis Using Multi-Hidden-Layer Extreme Learning Machine with Optimized Structure by Shan Pang, Xinyi Yang, Xiaofeng Zhang

“…A new aero gas turbine engine gas path component fault diagnosis method based on multi-hidden-layer extreme learning machine with optimized structure (OM-ELM) was proposed. OM-ELM employs quantum-behaved particle swarm optimization to automatically obtain the optimal network structure according to both the root mean square error on training data set and the norm of output weights. …”
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Node optimization coverage method under link model in passive monitoring system of three-dimensional wireless sensor network by Zhanjun Hao, Nanjiang Qu, Xiaochao Dang, Jiaojiao Hou

“…In the process of optimal coverage, the traditional genetic algorithm and particle swarm optimization algorithm are introduced and improved. …”
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A Distributed Economic Power Dispatch Strategy Considering State of Charge for Microgrids by Kaicheng Lu, Shufeng Dong, Yonghua Song

“…To improve the effectiveness of power distribution, an improved average consensus algorithm(IACA) based on particle swarm optimization (PSO) is proposed to adjust the weight matrix of communication networks, which reduces the number of iterations to estimate the average SoC. …”
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A comparative study of different kinematic wake models within metaheuristics for efficient wind farm layout optimization by Antonio J. Romero-Barrera, David Casillas-Pérez, Laura Cornejo-Bueno, Jorge Pérez-Aracil, Alvaro Paricio-Garcia, Miguel A. Lopez-Carmona, Juan Blanco-Sancho, Sujan Ghimire, Ravinesh C. Deo, Antonio J. Caamaño, Sancho Salcedo-Sanz

“…We analyze the performance of seven analytical wake models—Jensen, Park2, Frandsen, Larsen, Bastankhah, Ishihara, and Zhang—to estimate the downstream wind speed deficits included in the objective function of metaheuristics (Genetic Algorithm, Particle Swarm Optimization, and Coral Reefs Optimization with Substrate Layers), for an optimal WFLO solution. …”
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Hybrid GOA and PSO optimization for load frequency control in renewable multi source dual area power systems by Muhammad Zubair Yameen, Abdul Khalique Junejo, Zhigang Lu, Rizwan Aziz Siddiqui, Fayez F. M. El-Sousy, Ibtisam Naveed

“…To address these challenges, this paper proposes a novel Proportional-Integral-Derivative (PID) controller optimized using a hybrid Grasshopper Optimization Algorithm-Particle Swarm Optimization (GOA-PSO) approach. …”
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Optimizing Power Flow in Photovoltaic-Hybrid Energy Storage Systems: A PSO and DPSO Approach for PI Controller Tuning by Samira Heroual, Belkacem Belabbas, Yasser Diab, Mohamed Metwally Mahmoud, Tayeb Allaoui, Naima Benabdallah

“…The proposed control scheme is based on proportional-integral (PI) controllers optimized with particle swarm optimization (PSO) and duplicate particle swarm optimization (DPSO) algorithms. …”
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