Improving with Hybrid Feature Selection in Software Defect Prediction by Muhammad Yoga Adha Pratama, Rudy Herteno, Mohammad Reza Faisal, Radityo Adi Nugroho, Friska Abadi

“…This research focuses on the problems that occur in Particle Swarm Optimization (PSO), such as the problem of noisy attributes, high-dimensional data, and premature convergence. …”
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Structural Parameter Identification Using Multi-Objective Modified Directional Bat Algorithm by LIU Li-jun, LIN Ying-hai, SU Yong-hui, LEI Ying

“…Compared to Multi-Objective Particle Swarm Optimization （MOPSO） and the Non-Dominated Sorting Genetic Algorithm-II （NSGA-II）， MOMDBA outperformed its counterpart. …”
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A hybrid framework for heart disease prediction using classical and quantum-inspired machine learning techniques by Ankur Kumar, Sanjay Dhanka, Abhinav Sharma, Rohit Bansal, Mochammad Fahlevi, Fazla Rabby, Mohammed Aljuaid

“…Subsequently, both classical and quantum-inspired models are trained and optimized. The classical models utilized Genetic Algorithms (CGA) and Particle Swarm Optimization (CPSO) for hyperparameter tuning, while the quantum-inspired models employed Quantum Genetic Algorithms (QGAs) and Quantum Particle Swarm Optimization (QPSO). …”
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An Optimization Method for Multi-Functional Radar Network Deployment in Complex Regions by Yi Han, Xueting Li, Xiangliang Xu, Zhenxing Zhang, Tianxian Zhang, Xiaobo Yang

“…This paper addresses the deployment of a multi-functional radar network (MFRN) in complex regions that may exhibit non-connectivity, holes, or concave shapes, utilizing multi-objective particle swarm optimization (MOPSO). Unlike traditional approaches that rely on constraint-handling techniques, the proposed methodology leverages the unique characteristics of polygonal deployment regions to enhance deployment efficiency. …”
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Three-Dimensional Drone Cell Placement: Drone Placement for Optimal Coverage by Aniket Basu, Hooman Oroojeni, Georgios Samakovitis, Mohammad Majid Al-Rifaie

“…The multi-drone-cell placement problem is solved using adapted Dispersive Flies Optimization alongside other meta-heuristic algorithms such as Particle Swarm Optimization and differential evolution. …”
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On the Use of an Improved Artificial Fish Swarm Algorithm-Backpropagation Neural Network for Predicting Dam Deformation Behavior by Bo Dai, Hao Gu, Yantao Zhu, Siyu Chen, E. Fernandez Rodriguez

“…The hybrid model’s preciseness is verified against the radial displacements of a pendulum in a concrete arch dam and simulations of four models: statistical model, BP-ANN optimized by genetic algorithm (GA), particle swarm optimization (PSO), and AFSA. …”
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Unscented transformation method for robustness verification of helicopter flight control system by LIU Changqi, LI Aijun, DUAN Guangzhan, LI Zuo

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State-of-charge estimation for Lithium-Ion batteries using Kalman filters based on fractional-order models by Likun Xing, Liuyi Ling, Bing Gong, Menglong Zhang

“…The Fractional-Order Model (FOM) parameters and differentiation orders are identified by the Particle Swarm Optimization (PSO) algorithm, and a pulsed-discharge test is implemented to verify the accuracy of parameter identification. …”
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Dynamic Inversion Method for Concrete Gravity Dam on Soft Rock Foundation by Guanglin Yin, Chaoning Lin, Taozhen Sheng, Wenbo Xue, Tongchun Li, Siyu Chen

“…To address this limitation, an improved particle swarm optimization (PSO) algorithm is developed for dynamic parameter inversion, combining real-time monitoring data with finite element modeling to evaluate the time-varying elastic modulus of the foundation. …”
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Enhancing Frequency Event Detection in Power Systems Using Two Optimization Methods with Variable Weighted Metrics by Hussain A. Alghamdi, Midrar A. Adham, Umar Farooq, Robert B. Bass

“…The algorithm parameters were optimized using two well-established optimization techniques: Grey Wolf Optimization and Particle Swarm Optimization. …”
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Classification of biomedical lung cancer images using optimized binary bat technique by constructing oblique decision trees by Shobha Aswal, Neelu Jyothi Ahuja, Ritika Mehra

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Analysis of Customer Power Consumption Behavior Based on DPSO-Kmeans under the Ubiquitous Power Internet of Things by WANG Ying, XIANG Wen, ZHANG Qun, GAO Xiuyun

“…To this problem, an improved K-means algorithm (DPSO-Kmeans) based on an improved dynamic particle swarm optimization algorithm is proposed and used in the analysis of customers′ electricity consumption behavior. …”
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Optimization of Ship Permanent Magnet Synchronous Motor ADRC Based on Improved QPSO by Hongbo Xu, Jundong Zhang, Jiale Liu, Yang Cao, Ao Ma

“…To address the impact of load variations, external environmental changes, and the tuning of the parameters on Permanent Magnet Synchronous Motors (PMSMs) used in ships, this study proposes an Active Disturbance Rejection Control (ADRC) strategy for PMSMs, optimized by the Quantum-behaved Particle Swarm Optimization (QPSO) algorithm. …”
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Adaptive Control and Market Integration: Optimizing Distributed Power Resources for a Sustainable Grid by Josue N. Otshwe, Bin Li, Songsong Chen, Feixiang Gong, Bing Qi, Ngouokoua J. Chabrol

“…System performance is improved using advanced control strategies together with real-time market-responsive changes and predictive algorithms. The efficacy of the proposed methodology is validated through a detailed simulation of a small island grid using mixed-integer linear programming (MILP) and particle swarm optimization (PSO), which demonstrates significant operational improvements. …”
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SiFSO: Fish Swarm Optimization-Based Technique for Efficient Community Detection in Complex Networks by Yasir Ahmad, Mohib Ullah, Rafiullah Khan, Bushra Shafi, Atif Khan, Mahdi Zareei, Abdallah Aldosary, Ehab Mahmoud Mohamed

“…The proposed SiFSO algorithm’s performance is tested against state-of-the-art particle swarm optimization (PSO) algorithms in Q-modularity and normalized mutual information (NMI). …”
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Optimal Power Flow using An Optimally Tuned Pattern Search Algorithm by Firmansyah Nur Budiman, Taufal Hidayat, Rudi Uswarman

“…The performance of the OPS algorithm is evaluated based on objective function values and computation times and is compared with IPM and two popular metaheuristic techniques, particle swarm optimization (PSO) and genetic algorithm (GA). …”
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Sigmoid-Function-Based Adaptive Pelican Optimization Algorithm for Global Optimization by A. F. S. Yussif, S. Adjei, B. E. Wilson

“…Additionally, the MPOA outperformed other traditional optimization algorithms, such as Particle Swarm Optimization (PSO) and Genetic Algorithms (GA), in terms of achieving better optimization results. …”
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PSO-PID-based optimization and HIL verification method for the rear-mounted linkage adjustment of hilly-mountainous tractors by Yiwei Wu, Chengkang Yao, Mengnan Liu, Jingyun Zhang, Lin Wang, Xiaoxiao Du, Xianghai Yan

“…In this paper, a rear-mounted linkage device with independent control of dual hydraulic cylinders is designed, and an optimization method for rear suspension adjustment based on Particle Swarm Optimization (PSO) algorithm to optimize the PID parameters is proposed. …”
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Efficient Real-Time Cost Management in Renewable Energy-Powered Microgrid with Integrated Electric Vehicle Charging/Discharging Control by Swati Sharma, Ikbal Ali

“…Leveraging a unique hybridization of particle-swarm optimization (PSO) and grey wolf optimization (GWO), our approach dynamically orchestrates energy flow and EV charging schedules. …”
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Assessment of energy management and power quality improvement of hydrogen based microgrid system through novel PSO-MWWO technique by Hafiz Ghulam Murtza Qamar, Xiaoqiang Guo, Ehab Seif Ghith, Mehdi Tlija, Abubakar Siddique

“…In the quest to improve energy management systems (EMS) and enhance power quality, a bi-level optimization approach named Particle swarm optimization-Modified water wave optimization (PSO-MWWO) has been proposed. …”
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