Optimal Power Flow Based on a Metaheuristics Optimization Approach for the Iraqi Super High Voltages Network by Ali Almosawi, Mesut Cevik, Aysel Ersoy

“…In this work, the proposed approach uses genetic algorithm (GA) and camping the Hybrid Particle Swarm Optimization and Genetic algorithm (HPSO+GA) as an intelligent methods to perform optimal power flow. …”
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Mathematical modeling and optimization of the active suspension system of a 6x6 electric vehicle by Berk Aydoğan, Ahmet Yildiz

“…Three different methods were used for optimization: Genetic Algorithm (GA), Particle Swarm Optimization (PSE) and Differential Evolution (DE) Optimization. …”
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Maximum power point tracking of photovoltaic module based on Particle Swarm Optimization enhanced with Quasi-Newton method. by Montaser Abdelsattar, Hamdi Ali Mohamed, Mohamed A Ismeil, Ahmed A Zaki Diab

“…The proposed algorithm results show that MPP extraction has been done with a high-speed response and the best efficiency. …”
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Optimization of Backpropagation (BP) Weight Values Using Particle Swarm Optimization (PSO) to Predict KIP Scholarship Recipients by Dika Kurnia Nanda, Dian Palupi Rini

“…To overcome this, the Particle Swarm Optimization (PSO) algorithm is used to optimize the weights of the BP artificial neural network. …”
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Risk prediction of hyperuricemia based on particle swarm fusion machine learning solely dependent on routine blood tests by Min Fang, Chengjie Pan, Xiaoyi Yu, Wenjuan Li, Ben Wang, Huajian Zhou, Zhenying Xu, Genyuan Yang

“…The potential of using routine blood tests alone for prediction has not yet been explored. Therefore, this paper proposes a hyperuricemia risk prediction model that integrates Particle Swarm Optimization (PSO) with machine learning, which can accurately assess the risk of hyperuricemia by relying solely on routine blood data. …”
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Early breast cancer detection via infrared thermography using a CNN enhanced with particle swarm optimization by Riyadh M. Alzahrani, Mohamed Yacin Sikkandar, S. Sabarunisha Begum, Ahmed Farag Salem Babetat, Maryam Alhashim, Abdulrahman Alduraywish, N. B. Prakash, Eddie Y. K. Ng

“…Infrared thermography, by contrast, offers a non-invasive and economical alternative; however, its clinical adoption has been limited, largely due to difficulties in accurate thermal image interpretation and the suboptimal tuning of machine learning algorithms. …”
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Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms by Marwan Dhuheir, Aiman Erbad, Bechir Hamdaoui, Samir Brahim Belhaouari, Mohsen Guizani, Thang X. Vu

“…The integration of unmanned aerial vehicles (UAVs) in the Industrial Internet of Things (IIoT) for smart city applications has been gaining significant attention. UAV swarms are increasingly employed to monitor ground-based IIoT devices in smart cities, offering valuable support to situation-awareness IoT applications, such as surveillance, traffic management, and emergency response. …”
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REVIEW OF FEATURE SELECTION METHODS USING OPTIMIZATION ALGORITHM (Review paper for optimization algorithm) by Zana O. Hamad

“…Review of Nature-inspired algorithms that have been used for features selection is more focused such as particle swarm, Grey Wolf, Bat, Genetic, wale, and ant colony algorithm. …”
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Analysis on Solar Panel Crack Detection Using Optimization Techniques by M.D. Dafny Lydia, K. Sri Sindhu, K. Gugan

“…In view of the segmentation process, the potential regions which have cracks have been found, and then distinctive optimization algorithms were run on these areas to discover crack pixels. …”
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Clustering Credit Card Holder Berdasarkan Pembayaran Tagihan Menggunakan Improved K-Means dengan Particle Swarm Optimization by Farhanna Mar'i, Ahmad Afif Supianto

“…However, the K-Means method can not provide the optimum solution because of its limitation in determining the optimal centroid point, so to improve the K-Means method in this research is used one of the evolution algorithm namely Particle Swarm Optimization (PSO) to generate optimum centroid point used in k-means calculation process. …”
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An Algorithmic Framework for Multiobjective Optimization by T. Ganesan, I. Elamvazuthi, Ku Zilati Ku Shaari, P. Vasant

“…Various metaheuristic techniques such as differential evolution (DE), genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) have been used in conjunction with scalarization techniques such as weighted sum approach and the normal-boundary intersection (NBI) method to solve MO problems. …”
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Real-Time Trajectory Planning and Effectiveness Analysis of Intercepting Large-Scale Invading UAV Swarms Based on Motion Primitives by Yue Zhang, Xianzhong Gao, Jian’an Zong, Zhihui Leng, Zhongxi Hou

“…We have proposed an algorithmic framework based on three genetic operators for solving multi-target interception trajectories, offering certain advantages in terms of solution accuracy and speed compared to other optimization algorithms. …”
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Proposal of a novel particle swarm optimization for constrained optimization problems (1st report: Basic study with benchmark problems) by So FUKUHARA, Nobuhisa KATSUMATA, Masao ARAKAWA

“…To overcome the difficulties, this paper presents a novel particle swarm optimization algorithm named independent 2-group particle swarm optimization (I2GPSO). …”
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Competitive Elimination Improved Differential Evolution for Wind Farm Layout Optimization Problems by Sichen Tao, Yifei Yang, Ruihan Zhao, Hiroyoshi Todo, Zheng Tang

“…Therefore, metaheuristic algorithms with inherent discrete characteristics like genetic algorithms (GAs) and particle swarm optimization (PSO) have been extensively developed into current state-of-the-art WFLOP optimizers. …”
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A State-of-the-Art Fractional Order-Driven Differential Evolution for Wind Farm Layout Optimization by Sichen Tao, Sicheng Liu, Ruihan Zhao, Yifei Yang, Hiroyoshi Todo, Haichuan Yang

“…The wind farm layout optimization problem (WFLOP) aims to maximize wind energy utilization efficiency and mitigate energy losses caused by wake effects by optimizing the spatial layout of wind turbines. Although Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) have been widely used in WFLOP due to their discrete optimization characteristics, they still have limitations in global exploration capability and optimization depth. …”
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A Novel Chaotic Particle Swarm Optimized Backpropagation Neural Network PID Controller for Four-Switch Buck–Boost Converters by Luoyao Ren, Dazhi Wang, Xin Yan, Yupeng Zhang, Jiaxing Wang

“…To address these challenges, chaotic optimization algorithms are integrated with BPNN. The chaotic particle swarm optimization (CPSO) algorithm enhances the global search capability, enabling a faster system response and minimizing overvoltage. …”
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Deep and Domain Specific Feature-Based Cervical Cancer Classification Using Support Vector Machine Optimized With Particle Swarm Optimization by Ritesh Maurya, Lucky Rajput, Satyajit Mahapatra

“…The noisy features have been eliminated by utilising the concept of mutual information whereas, a support vector machine optimized with Particle Swarm Optimization (PSO) was used for the classification. …”
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Enhanced Anti-Lock Braking System Performance: A Comparative Study of Adaptive Terminal Sliding Mode Control Approaches by Salma Khatory, Houcine Chafouk, El Mehdi Mellouli

“…Additionally, Adaptive Switching Control (ASC) based on Particle Swarm Optimization (PSO) is applied to achieve faster convergence, suppress chattering, and enhance system robustness. …”
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An Improved Squirrel Search Algorithm for Optimization by Tongyi Zheng, Weili Luo

“…Squirrel search algorithm (SSA) is a new biological-inspired optimization algorithm, which has been proved to be more effective for solving unimodal, multimodal, and multidimensional optimization problems. …”
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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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