A Semi-Trailer Path Planning Method Considering the Surrounding Traffic Conditions and Vehicle Roll Stability by Haochuan Zhang, Zhigen Nie, Yufeng Lian

“…Subsequently, we apply a particle swarm optimization algorithm to enhance the B-spline curve. …”
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An Adaptive Control Strategy for a Virtual Synchronous Generator Based on Exponential Inertia and Nonlinear Damping by Huiguang Pian, Keqilao Meng, Hua Li, Yongjiang Liu, Zhi Li, Ligang Jiang

“…Control parameters are optimized using an enhanced particle swarm optimization (PSO) algorithm based on a composite performance index that accounts for frequency deviation, overshoot, settling time, and power tracking error. …”
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Adaptive Exploration Artificial Bee Colony for Mathematical Optimization by Shaymaa Alsamia, Edina Koch, Hazim Albedran, Richard Ray

“…The artificial bee colony (ABC) algorithm is a famous swarm intelligence method utilized across various disciplines due to its robustness. …”
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Harmonic Analysis of Radial Distribution Systems Embedded Shunt Capacitors by Abdallah Elsherif, Tamer Fetouh, Hasan Shaaban

“…Therefore, in this paper, a new proposed multi-objective particle swarm optimization "MOPSO" for optimal capacitors placement on harmonic polluted distribution systems has been introduced. …”
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Study on the Reconstruction of the Spectral Pattern of Near-Island Reef Bimodal Waves by Weihang Sun, Yuguo Pei, Leilei Qu, Xiaobo Wang

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Comprehensive Evaluation of Bankruptcy Prediction in Taiwanese Firms Using Multiple Machine Learning Models by Hung V. Pham, Tuan Chu, Tuan M. Le, Hieu M. Tran, Huong T.K. Tran, Khanh N. Yen, Son V. T. Dao

“…Additionally, a wrapper-based feature selection (FS) utilizing Binary Particle Swarm Optimization (BPSO) was utilized to find an optimal feature subset and boost the model’s predictive performance. …”
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Stability analysis of semi-submersible floating wind turbines based on gyro-turbine coupled dynamics model by Wancheng Wang, Hao Li, Yihang Yang, Kai Sheng, Lijing Chen

“…Based on this model, an innovative PSO-optimized fuzzy control strategy is proposed, utilizing intelligent particle swarm optimization algorithms to adjust controller parameters for optimal performance under various environmental conditions. …”
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Enhancing Wind Turbine Efficiency: An Experimental Investigation of a Sensorless Three-Vector Finite Set Predictive Torque Control Approach for PMSG-Based Systems by Marouane Ahmed Ghodbane, Toufik Mohamed Benchouia, Mohamed Chebaani, Mohamed Becherif, Yassine Himeur, Amar Golea, Abdelmoumen Ghilani, Zakaria Alili, Shadi Atalla, Wathiq Mansoor

“…This paper presents a new control strategy that combines two intelligent estimation techniques—the Extended Kalman Filter (EKF) and Particle Swarm Optimization (PSO)—with Three-Vector Finite Set Predictive Torque Control (3V FS-PTC). …”
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Sensorless real-time solar irradiance prediction in grid-connected PV systems using PSO-MPPT and IoT-enabled monitoring by Ali Zaki Mohammed Nafa, Adel A. Obed, Ahmed J. Abid, Salam J. Yaqoob, Mohit Bajaj, Mohammad Shabaz

“…The approach leverages the maximum power point current ( $$\:{\text{I}}_{\text{mpp}}$$ ) and voltage ( $$\:{\text{V}}_{\text{mpp}}$$ ) measured directly from a PV module to predict irradiance, utilizing a Particle Swarm Optimization (PSO)-based Maximum Power Point Tracking (MPPT) algorithm to ensure accurate tracking of power output across varying irradiance levels. …”
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Optimal Power Generation from Bagasse in a Sugarcane Plant using PSO Algorithm Compared to SQP Algorithm by Mohammad Askari Khanabadi, Imaneh Dehghani, Shahrokh Shojaeian

“…Due to the high amounts of sugarcane residue or bagasse which was produced by sugarcane plants in Iran, this study was aimed to optimize power generation from bagasse biomass in sugarcane plants using Particle Swarm Optimization (PSO) algorithm by data obtained from several case studies which had been simulated with SQP (Sequential quadratic programming) algorithm. …”
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Fuzzy LQR-based control to ensure comfort in HVAC system with two different zones by Elif Çinar, Tayfun Abut

“…The core novelty of this work lies in the development and comparison of advanced control algorithms, including the Linear Quadratic Regulator (LQR), a Particle Swarm Optimization (PSO)-based LQR, and a newly designed PSO-based Fuzzy LQR (FLQR) controller. …”
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A black-winged kite optimization algorithm enhanced by osprey optimization and vertical and horizontal crossover improvement by Yancang Li, Binli Shi, Weitao Qiao, Zunfeng Du

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Path Optimization Strategy for Unmanned Aerial Vehicles Based on Improved Black Winged Kite Optimization Algorithm by Shuxin Wang, Bingruo Xu, Yejun Zheng, Yinggao Yue, Mengji Xiong

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Optimization of Offshore Wind and Wave Energy Co-Generation System Based on Improved Seagull Optimization Algorithm by Xiaoshi Zhuang, Honglue Wan, Dongran Song, Xinyu Fan, Yuchen Wang, Qian Huang, Jian Yang

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Exploring the Orca Predation Algorithm for Economic Dispatch Optimization in Power Systems by Vivi Aida Fitria, Arif Nur Afandi, Aripriharta

“…This research shows that Orca Predation Algorithm consistently does better than other bio-inspired algorithms like Particle Swarm Optimization, Whale Optimization Algorithm, Grey Wolf Optimizer, the Bat Algorithm, Genetic Algorithm and Ant Colony Optimization in terms of minimum cost, average cost, and solution stability. …”
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Deep Reinforcement Learning-Based Motion Control Optimization for Defect Detection System by Yuhuan Cai, Liye Zhao, Xingyu Chen, Zhenjun Li

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Optimal Trajectory Optimization of 7R Robot for Space Maintenance Operation by Qidong Li, Hehua Ju, Pengfei Xiao, Feifei Chen, Fei Lin

“…Finally, a hybrid optimization algorithm is proposed to solve the trajectory optimization problem of space robots by combining genetic algorithm and particle swarm optimization method. …”
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Improved Firefly Algorithm Based on Heuristic Information by CUI Jia-rui, LI Qing, YANG Liu-yi, WANG Heng, ZHANG Bo-yu

“…Firefly Algorithm (FA) is an optimization algorithm based on swarm intelligence which mimics the social behavior of fireflies based on the flashing and attraction characteristics of fireflies With the aim to address the disadvantages of the firefly algorithm of slow convergence speed and ease of falling into the local optimum in the later period of the evolution process, the firefly algorithm is improved herein Two kinds of heuristic information are proposed into the algorithm to guide the convergence of the algorithm The first one takes the current global best as the heuristic information referencing the “global optimal” idea in particle swarm optimization, therefore, an algorithm called FAGO (Firefly Algorithm based on Global Optimization) is formed The second one is called FABE (Firefly Algorithm based on Bayesian Estimation) using the optimal moving direction calculated by Bayesian estimation as heuristic information The improved algorithms in this study are applied to numerical simulations of several classical test functions and compared with traditional FA and some other′s research are carried out The simulation results show that the proposed algorithms can well accelerate the convergence speed and improve the convergence accuracy…”
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Optimization method of truss structure size and shape based on harmonic search genetic algorithm by XIE Jun, ZHANG Huashuai, LIN Shuqin, PANG Bolei, YAN Jie

“…Compared with genetic algorithm (GA), heuristic particle swarm optimization (HPSO) and other optimization algorithms, the optimization effect is obvious, and it is a method suitable for the shape optimization of truss structure.…”
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Exploring Evolutionary Algorithms for Multi-Objective Optimization in Seismic Structural Design by Seda Göktepe Körpeoğlu, Süleyman Mesut Yılmaz

“…In particular, evolutionary algorithms such as genetic algorithms and particle swarm optimization are used to optimize the performance of structures to meet seismic loads. …”
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