Design of Cloud-Based Complex VR 3D Scene Interaction Based on Attribute Preferences by Ze Yu Yang, Yeom Jun Young

“…The study leverages Reinforcement Learning (RL) and Particle Swarm Optimization (PSO) to address critical challenges such as user interface adaptability and cloud resource allocation. …”
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A systematic review on search‐based test suite reduction: State‐of‐the‐art, taxonomy, and future directions by Amir Sohail Habib, Saif Ur Rehman Khan, Ebubeogu Amarachukwu Felix

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Ship Formation and Route Optimization Design Based on Improved PSO and D-P Algorithm by Peilong Xu, Dan Lan, Haolin Yang, Shengtian Zhang, Hyeonseok Kim, Incheol Shin

“…Based on this, a ship formation model combining improved particle swarm optimization algorithm and a generative route optimization method based on improved Douglas-Peucker algorithm are proposed. …”
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VMD‐FBCCA classification method for SSVEP brain–computer interfaces by Ping Tan, Fengsheng Wang, Kaijun Zhou, Yi Shen

“…Next, a particle swarm algorithm is employed to optimize the weights of the IMFs and reconstruct the EEG signals. …”
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Complexity Reduction in the Use of Evolutionary Algorithms to Function Optimization: A Variable Reduction Strategy by Guohua Wu, Witold Pedrycz, Haifeng Li, Dishan Qiu, Manhao Ma, Jin Liu

“…In this study, VRS is combined with particle swarm optimization variants and tested on several benchmark optimization functions and a real-world optimization problem. …”
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Time-optimal trajectory planning for excavators operating arm based on SA-PSO algorithm by ZHANG Yunyue, ZHAO Zhicheng, YANG Kai, ZHANG Yu, YANG Jiangtao

“…ObjectiveIn view of the problems of unstable operation, low optimization efficiency and falling into local optimum when optimizing the operation trajectory with a single intelligent algorithm, this paper proposes to combine simulated annealing and particle swarm optimization (SA-PSO) to perform optimal time planning for the excavation task trajectory of the excavator operating arm.MethodsFirstly, in the D-H coordinate system, the mechanism diagram of the excavator operating arm is constructed to establish its kinematic model; secondly, the 4-3-3-3-4 piecewise polynomial is used for interpolation, and the SA-PSO algorithm is used to optimize the high-efficiency excavation task trajectory under the constraints of joint velocity and acceleration; finally, under the same operation task, the differential evolution algorithm (DE) and particle swarm optimization algorithm (PSO) are used in turn to obtain the time optimal trajectory.ResultsThe experimental results show that the optimal time trajectory obtained by the hybrid algorithm has shorter operation efficiency and the smallest impact, which can effectively reduce the wear of each joint hydraulic cylinder. …”
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Machine Learning-Based Modeling with Optimization Algorithm for Predicting Mechanical Properties of Sustainable Concrete by Muhammad Izhar Shah, Shazim Ali Memon, Muhammad Sohaib Khan Niazi, Muhammad Nasir Amin, Fahid Aslam, Muhammad Faisal Javed

“…In this research, multiexpression programming (MEP) has been employed to model the compressive strength, splitting tensile strength, and flexural strength of waste sugarcane bagasse ash (SCBA) concrete. Particle swarm optimization (PSO) algorithm was used to fine-tune the hyperparameter of the proposed MEP. …”
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APPLICATION OF SEMI SUPERVISED LAPLACE SCORE IN ROLLING BEARING FAULT DIAGNOSIS (MT) by LIANG Chuang, CHEN ChangZheng, LIU Ye, JIA XinYing

“…SSLS applies the semi supervised idea to the Laplace score feature selection method, uses a small number of labeled samples and a large number of unlabeled samples, and combines KPCA to excavate fault features for a second time. At the same time, particle swarm optimization-based support vector machine（PSO-SVM） algorithm is used for fault classification. …”
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Day-Ahead Scheduling for Economic Dispatch of Combined Heat and Power With Uncertain Demand Response by Seyyed Ebrahim Hosseini, Mojtaba Najafi, Ali Akhavein, Mahdi Shahparasti

“…The above problem is solved through the use of the co-evolutionary particle swarm optimization (C-PSO) algorithm and the proposed model is implemented on a standard seven-unit system for a period of 24 hours.…”
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A hybrid deep learning and differential evolution approach for accurate fake news detection by Shailendra Pratap Singh, Naween Kumar, Gyanendra Kumar, Ahamed Shafeeq B.M.

“…Experimental results on benchmark datasets demonstrate that the hybrid approach achieves superior accuracy, precision, recall, and F1-score compared to existing methods such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and standalone deep learning models. …”
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A High‐Performance MPPT Solution for Solar DC Microgrids: Leveraging the Hippopotamus Algorithm for Greater Efficiency and Stability by Debabrata Mazumdar, Taha Selim Ustun, Chiranjit Sain, Ahmet Onen

“…Performance of HA's is compared with three established optimization algorithms: Grey Wolf Optimization, Cuckoo Search Algorithm and Particle‐Swarm Optimization across different operating scenarios and partial shading circumstances. …”
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Robust Framework for PMU Placement and Voltage Estimation of Power Distribution Network by Nida Khanam, Mohd. Rihan, Salman Hameed

“…The suggested method uses a hybrid Multi-Objective Particle Swarm Optimization and Differential Evolution (MOPSO-DE) algorithm to find the best PMU positions and the Weighted Least Squares (WLS) method to estimate voltage magnitude. …”
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New method for landslide susceptibility evaluation in alpine valley regions that considers the suitability of InSAR monitoring and introduces deformation rate grading by Dingyi Zhou, Zhifang Zhao, Wenfei Xi, Xin Zhao, Jiangqin Chao

“…The landslide susceptibility model is developed utilizing the Particle Swarm Optimization-Back Propagation (PSO-BP) algorithm. …”
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Optimizing Solid Oxide Fuel Cell Performance Using Advanced Meta-Heuristic Algorithms by Siva Ram Rajeyyagari, Srinivas Nowduri

“…These include the Angle of Attack Optimization (AOA), Particle Swarm Optimization with Grey Wolf Optimizer (PSOGWO), Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Moth Flame Optimization (MFO), and Multi-Verse Optimizer (MVO). …”
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Research on bearing fault diagnosis based on improved northern goshawk algorithm optimizing SVM by WU Xiaojun, LI Quwei

“…In order to evaluate the performance of the improved algorithm, firstly, benchmark testing functions were used for experiments, and the improved algorithm was compared with existing optimization algorithms such as NGO, particle swarm optimization (PSO), sparrow search algorithm (SSA), etc. …”
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A New Bipolar Approach Based on the Rooster Algorithm Developed for Utilization in Optimization Problems by Mashar Cenk Gençal

“…Then, the performance of the BIRA algorithm was compared with the performances of meta-heuristic algorithms widely used in the literature, Standard Genetic Algorithm (SGA), Differential Evolution (DE), Particle Swarm Optimization (PSO), Cuckoo Search (CS), and Grey Wolf Optimizer (GWO), and thus, its success in the literature was tested. …”
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Quadrotor Robust Fractional-Order Control Based on a Recent Bonobo Optimization Algorithm by Faycal Ziani, Aissa Benhammou, Mohamed Amine Hartani, Hegazy Rezk

“…The five fractional parameters for each engine are also improved using the Bonobo Optimization (BO) algorithm. The optimized results in this paper are compared with the algorithms used, such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO). …”
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Algorithm PSO for maximum coverage of users using drones to find optimal points for deployment by Fariborz Rasouli

“…For this reason, using the Particle Swarm Optimization (PSO) algorithm, we try to introduce drones as ABS to find the maximum coverage of users in the shortest possible time. …”
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Joint Optimization Algorithm for UAV-Assisted Caching and Charging Based on Wireless Energy Harvesting by Yumeng Zhu, Qi Zhu

“…The joint optimization problem is divided into three subproblems, which use the Lagrange multiplier method, a simulated annealing algorithm, and a particle swarm optimization algorithm. …”
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Spatio-Temporal Optimization of Long-term Groundwater Monitoring Networks Using PSO Algorithm by Mohammad Mirzavand, Seyyed Javad Sadatinejad, Hamid Kardan Moghaddam

“…In this study, several groundwater quality parameters (EC, SAR, TH, TDS, pH, K, Na+, Ca2+, Mg2+, SO42-, HCO3-, and Cl-) for 113 samples sites clustered based on the particle swarm optimization (PSO) algorithm to significantly decrease cost and save time in LTM. …”
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