Multi-UAV DMPC Cooperative Guidance with Constraints of Terminal Angle and Obstacle Avoidance by Zijie Jiang, Xiuxia Yang, Cong Wang, Yi Zhang, Hao Yu

“…Based on the above design, a complete implementation process of the guidance scheme is presented, in which each UAV uses the particle swarm optimization algorithm to solve the preprocessed local optimization problem, and only the shared information among neighbors is utilized for calculation. …”
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A hybrid approach for investigation of electrical characteristics for rod to point electrode in gas insulators by R. Bharanidharan, V. J. Vijayalakshmi, R. V. Maheswari

“…The performance of the proposed method is put into practice on the MATLAB platform and contrasted with methods that are currently in use. Particle swarm optimization (PSO), heap-based optimizer (HBO), and wild horse optimizer (WHO) all yield inferior results compared to the proposed strategy. …”
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An Improved Multiobjective PSO for the Scheduling Problem of Panel Block Construction by Zhi Yang, Cungen Liu, Xuefeng Wang, Weixin Qian

“…An improved multiobjective particle swarm optimization called MOPSO-M is developed to solve the scheduling problem. …”
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Evaluation and Analysis of Land Input-Output Comprehensive Benefit Based on Fuzzy Mathematics and Analytic Hierarchy Process by Xincheng Zhu, Yan Zhang, Yunzhi Hou, Minda Jiang

“…Then, based on the theory of fuzzy mathematics, the improved particle swarm optimization (PSO) algorithm is used to identify the fuzzy density value of the evaluation index. …”
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Electricity Theft Detection in a Smart Grid Using Hybrid Deep Learning-Based Data Analysis Technique by Camille Franklin Mbey, Jacques Bikai, Felix Ghislain Yem Souhe, Vinny Junior Foba Kakeu, Alexandre Teplaira Boum

“…Thus, the proposed hybrid model is based on the support vector machine (SVM) and a particle swarm optimization (PSO) algorithm to detect energy fraudsters in the network. …”
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Piecewise Model and Parameter Obtainment of Governor Actuator in Turbine by Jie Zhao, Li Wang, Dichen Liu, Jun Wang

“…Several testing functions are selected to compare genetic algorithm and particle swarm optimization algorithm (GA-PSO) with other basic intelligence algorithms. …”
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A Novel Method of Self-Healing Concrete to Improve Durability and Extend the Service Life of Civil Infrastructure by Yan Xue, Weiliang Gao, Yanming Zhao

“…Moreover, a concrete durability prediction model based on particle swarm optimization-least squares support vector machine (PSO-LSSVM) and improved NSGA-II (nondominated sorting genetic algorithm II) algorithm was proposed to quickly and accurately determine the optimization scheme of self-healing concrete mix proportion. …”
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Tent–PSO-Based Unmanned Aerial Vehicle Path Planning for Cooperative Relay Networks in Dynamic User Environments by Shuyue Liu, Wenmao Zhou, Mingwei Qin, Xin Peng

“…The proper planning of UAV paths can improve user coverage while maintaining communication quality. The traditional particle swarm optimization (PSO) algorithm exhibits strong global search capabilities; however, it suffers from challenges such as uneven search coverage owing to the random distribution of the initial particle positions. …”
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Binary atom search optimisation approaches for feature selection by Jingwei Too, Abdul Rahim Abdullah

“…The particle swarm optimisation (PSO), binary differential evolution (BDE), binary bat algorithm (BBA), binary flower pollination algorithm (BFPA), and binary salp swarm algorithm (BSSA) are used to evaluate the efficacy and efficiency of proposed approaches in feature selection. …”
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Dynamic energy consumption monitoring and scheduling for green buildings: A comprehensive approach by Hua Zheng, Pengming Wang

“…Meanwhile, the particle swarm optimization (PSO) algorithm is used to solve the multi-objective scheduling problem to achieve the global objectives of energy conservation, cost reduction, and comfort optimization. …”
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Model Updating and Global Eigenvalue Analysis of a Tie-Bolt Rotor Using Zero-Length Contact Elements under Different Preloads by Pu Li, Qi Yuan

“…Model updating is carried out to tune the contact parameters using the Particle Swarm Optimization algorithm. Furthermore, a global eigenvalue evaluation is carried out to demonstrate the impact of the lumped spring-damper element on the modal results. …”
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Robust Analysis and Parameters Identification of the Nonlinear Multistage Dynamical System in Batch Fermentation of Glycerol by Xu Zhang, Xinying Wang, Enmin Feng, Zhilong Xiu

“…Then we establish a parameter identification model and construct the particle swarm optimization algorithm to solve it. …”
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Breaking time control of back-to-back double E-type alternating current contactor by Lei Qi, Ming Zong, Shuyi Hao, Xuejie Wang

“…A back-to-back double-E alternating current contactor is proposed, and its structural parameters are optimized by particle swarm optimization algorithm. …”
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Prediction and evaluation of residual life of casing with corrosion defects by JIA Aoyin, QIAN Liqin, WANG Jie, YANG Jingwei, WU Yaokun, WEI Mingji

“…Therefore, there is an urgent need to conduct residual life and safety evaluations of old oil field casings.MethodsBased on the von Mises equivalent stress yield criterion, a three-dimensional finite element calculation model of casings containing corrosion defects was established to analyze the influence law of corrosion pit depth and angle on casing stress distribution. The particle swarm optimization-gaussian process regression （PSO-GPR) algorithm was employed to construct a predictive model for casing corrosion rates.ResultsIntegration of the two models, the evaluation of the residual life of casings with corrosion defects was completed, it has theoretical guidance significance for the prevention and management of corroded casings in oil field operations.…”
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Human activity recognition via smart-belt in wireless body area networks by Yuhong Zhu, Jingchao Yu, Fengye Hu, Zhijun Li, Zhuang Ling

“…Then a multi-classification Support Vector Machine algorithm optimized by Particle Swarm Optimization is applied to identify five kinds of conventional human postures. …”
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Acoustic Signal Aided Detection Method of Spiral Bevel Gears Based on PSO-MCKD by Li Xianshan, Tian Yu, Wei Lilin, Zhao Xiaofeng, Yan Changfeng

“…Combining the gear rolling inspection machine with the developed acoustic signal acquisition system, a real-time acoustic signal acquisition experiment is designed for detecting the quality of the contact marks on the tooth surface of the spiral bevel gear. Combined with the particle swarm optimization(PSO) algorithm and the maximum correlated kurtosis deconvolution(MCKD) based signal processing methods, the effect of different axial deviations on the gear mesh acoustic signals is investigated. …”
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A vibration signal processing method based on SE-PSO-VMD for ultrasonic machining by Honghuan Chen

“…This method is complemented by Particle Swarm Optimization (PSO) algorithm to optimize the number of IMFs and penalty factor, with Sample Entropy (SE) serving as a fitness function. …”
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Real-Time Height Measurement for Moving Pedestrians by Wenju Zhou, Fulong Yao, Wei Feng, Haikuan Wang

“…Secondly, a difference-particle swarm optimization (D-PSO) algorithm is proposed to remove the complex background and reduce the noises. …”
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An integrated approach of feature selection and machine learning for early detection of breast cancer by Jing Zhu, Zhenhang Zhao, Bangzheng Yin, Canpeng Wu, Chan Yin, Rong Chen, Youde Ding

“…The efficacy of the proposed method was assessed using five machine learning models, K-Nearest Neighbor (KNN), Random Forest (RF), Logistic Regression (LR), Support Vector Machine (SVM), and Light Gradient Boosting Machine (LightGBM), applied to the Wisconsin Breast Cancer Diagnosis (WBCD) datasets. Optimizing hyperparameters of five models using the Particle Swarm Optimization (PSO) algorithm. …”
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Deep Reinforcement Learning-Based Adaptive Nulling in Phased Array Under Dynamic Environments by Ying-Dar Lin, Jen-Hao Chang, Yuan-Cheng Lai

“…Traditional heuristic optimizers—such as Particle Swarm Optimization (PSO) and Genetic Algorithms (GA)—struggle to keep up because their iterative searches depend on pre-computed configurations that are unrealistic to obtain on the fly. …”
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