Damage Identification in Bars with a Wave Propagation Approach: Performance Comparison of Five Hybrid Optimization Methods by R.A. Tenenbaum, L.T. Stutz, K.M. Fernandes

“…The hybridization is performed combining the deterministic Levenberg-Marquardt method and each one of the following stochastic techniques: The Particle Swarm Optimization; the Luus-Jaakola optimization method; the Simulated Annealing method; the Particle Collision method; and a Genetic Algorithm. …”
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Uncertainty aware energy management in microgrids with integrated electric bicycle charging stations and green certificate market by Hossein Shayeghi, Iraj Faraji Davoudkhani

“…MTBO is benchmarked against particle swarm optimization, achieving a 21.6% reduction in operational costs and a 13.12% reduction in emissions in deterministic scenarios. …”
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Multiobjective Optimization of Large-Scale EVs Charging Path Planning and Charging Pricing Strategy for Charging Station by Weicheng Hou, Qingsong Luo, Xiangdong Wu, Yimin Zhou, Gangquan Si

“…Then, a particle swarm optimization (PSO) algorithm is applied to solve the optimal solution of charging station pricing designation. …”
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Identification of significant bio-markers from high-dimensional cancerous data employing a modified multi-objective meta-heuristic algorithm by Prajna Paramita Debata, Puspanjali Mohapatra

“…Here, the suggested algorithm has been compared with multi-objective chaotic Genetic Algorithm (MOCGA), multi-objective chaotic particle swarm optimization (MOCPSO), multi-objective Jaya (MOJaya), multi-objective PSO (MOPSO), and non-dominated sorting GA (NSGA-II) models. …”
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Enhancing Load frequency control in power systems using Puma Optimizer – Proportional Integral Derivative Method by Trung Kien Do, Thanh Long Duong

“…The simulation results show that the integral time absolute error (ITAE) value of the proposed PO method is smaller by 5.25%, 18.16%, 28.35%, and 59.92% compared to Particle Swarm Optimization (PSO), Crested Porcupine Optimization (CPO), Newton-Raphson-based optimization (NRBO), and Global Neighborhood Algorithm (GNA), respectively. …”
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Optimizing Joint Decisions of Dynamic Pricing and Ticket Allocation for High-Speed Railway with Operators’ Risk Preference by Huaqin Meng, Zhenying Yan, Yu Wang, Yiwei Xu

“…Then, the combination algorithm of particle swarm optimization algorithm and mixed-integer linear programming was designed to solve the model. …”
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Linear Active Disturbance Rejection Control System for the Travel Speed of an Electric Reel Sprinkling Irrigation Machine by Lingdi Tang, Wei Wang, Chenjun Zhang, Zanya Wang, Zeyu Ge, Shouqi Yuan

“…To enhance the robustness of the control system, it is necessary to investigate new disturbance rejection control algorithms and their effects. Therefore, a kinematic model of the reel sprinkling irrigation machine and a brushless DC (BLDC) motor model were established, and a linear active disturbance rejection control (LADRC) strategy based on improved particle swarm optimization (IPSO) was proposed. …”
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Power Frequency Oscillation Suppression Using Two-Stage Optimized Fuzzy Logic Controller for Multigeneration System by Y. K. Bhateshvar, H. D. Mathur

“…A comparison between genetic algorithm optimized PID controller (GA-PID), particle swarm optimized PID controller (PSO-PID), and proposed two-stage based PSO optimized fuzzy logic controller (TSO-FLC) is presented. …”
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Designing an explainable bio-inspired model for suspended sediment load estimation: eXtreme Gradient Boosting coupled with Marine Predators Algorithm by Roozbeh Moazenzadeh, Okan Mert Katipoğlu, Ahmadreza Shateri, Hamid Nasiri, Mohammed Abdallah

“…The superiority of the proposed model (XGB-MPA) compared to two other hybrid models, including XGB-PSO (Particle Swarm Optimization) and XGB-GWO (Grey Wolf Optimization) was also investigated. …”
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Optimal design and operation of a wind farm/battery energy storage considering demand side management by Siyu Tao, Chaohai Zhang, Andrés E. Feijóo‐Lorenzo, Victor Kim

“…It is tackled by the mixed‐discrete particle swarm optimization algorithm. The multi‐objective optimization problem (MOOP) model in the second level determines the operation schedule of the WF/BES and other generators taking the DSM into consideration. …”
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Control Optimization of a Hybrid Magnetic Suspension Blood Pump Controller Based on the Finite Element Method by Teng Jing, Yu Yang, Weimin Ru

“…The finite element method (FEM) was employed to optimize the physical parameters of the system. Based on this optimization, two intelligent PID tuning strategies—particle swarm optimization (PSO) and backpropagation (BP) neural networks—were compared. …”
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Hybrid Optimization based on Deep Learning Approach for Short-Term Load Forecast of Electricity Demand in Buildings by Charan Sekhar Makula, Ratna Dahiya

“…The performance of the BiLSTM technique is improved by using the optimally determined hyperparameters via a hybrid optimization algorithm that combines particle swarm optimization (PSO) and grey wolf optimization (GWO). …”
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Optimization and Modeling of Optical Emission Spatial Coverage from Underwater Multi-Faceted Optical Base Stations by Junjie Shi, Chunbo Ma, Xu Tian, Hanjun Guo, Jun Ao

“…Additionally, a Multi-Objective Particle Swarm Optimization (MOPSO) algorithm is used to optimize the configuration of the multi-faceted LED array by adjusting the deflection angles of the LED arrays and the emission half-angle of the LEDs at the OBS. …”
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Novel machine learning driven design strategy for high strength Zn Alloys optimization with multiple constraints by Chenfeng Pan, Wenwen Lin, Jianxing Zhou, Wei Jian, Ka Chun Chan, Yuk Lun Chan, Lu Ren

“…Interpretability analysis of the models was performed using the SHAP method with particle swarm optimization (PSO). Furthermore, a ML-based Zn alloy composition design system (ZACDS) was proposed by integrating the Bayesian optimization algorithm. …”
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Fractional Order Accumulation NGM (1, 1, k) Model with Optimized Background Value and Its Application by Jun Zhang, Yanping Qin, Xinyu Zhang, Bing Wang, Dongxue Su, Huaqiong Duo

“…The particle swarm optimization algorithm is used to estimate the parameters of the proposed model. …”
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Multi-Objective Optimization of Parking Charging Strategy for Extended-Range Hybrid Electric Vehicle Based on MOMSA by Rong Yang, Jianxiang Lu, Zhiqi Sun, Wei Huang

“…Furthermore, the MOMSA-based charging strategy outperforms a Multi-Objective Particle Swarm Optimization (MOPSO)-based approach, achieving comparable degradation mitigation while significantly reducing charging time. …”
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Design of a meta-heuristic artificial intelligence (AI) model for an optimal photovoltaic module cooling system by Armel Zambou Kenfack, Symphorien Tchimoe Kemle, Modeste Kameni Nematchoua, Venant Sorel Chara-Dackou, Elie Simo, Hermann Djeudjo Temene

“…The advantages and disadvantages of each method imply an efficient method for optimal selection. Therefore, this paper aims to design a multi-objective particle swarm optimization (MOPSO) model to search for a better configuration of cooled PV/T. …”
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An Adaptive Obstacle Avoidance Model for Autonomous Robots Based on Dual-Coupling Grouped Aggregation and Transformer Optimization by Yuhu Tang, Ying Bai, Qiang Chen

“…By placing observation points near critical obstacles, this strategy refines obstacle recognition, thus improving segmentation accuracy and flexibility in dynamic motion planning. The particle swarm optimization (PSO) algorithm is incorporated to optimize the attractive and repulsive gain coefficients of the artificial potential field (APF) methods. …”
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Optimized exposer region-based modified adaptive histogram equalization method for contrast enhancement in CXR imaging by Shivam Gangwar, Reeta Devi, Nor Ashidi Mat Isa

“…This study presents an advanced Exposure Region-Based Modified Adaptive Histogram Equalization (ERBMAHE) method, further optimized using Particle Swarm Optimization (PSO) to enhance contrast, preserve brightness, and strengthen fine details. …”
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Multi-objective Optimization of Combined Gray-green Infrastructure Rainwater System for Yuhuazhai Depot of Xi’an Metro by LYU Jiajie

“…Combined with the particle swarm optimization algorithm, the Matlab software is used to optimize the configuration of the green infrastructure within the depot in order to achieve effective control over the total runoff volume, peak flood, TSS (total suspended solids) and costs. …”
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