Energy Efficiency Optimization for UAV Distribution and Resource Allocation in NOMA and Multi-UAV Assisted Wireless Networks by Yuan Ren, Jieyu Wang, Yulong Xiao, Xuewei Zhang, Fan Jiang, Junxuan Wang, Jing Jiang, Guangyue Lu

“…At the same time, each GU group is assigned a serving UAV based on improved particle swarm optimization (PSO) algorithm. A system energy efficiency (EE) maximization problem is then formulated by jointly optimizing the UAV space locations as well as the transmit powers of GUs and UAVs. …”
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Gray Wolf Optimizer With Communication Strategy Based on DV-Hop for Nodes Location of Wireless Sensor Networks by Dan Yu, Ting Yuan, Haiyin Qing, Wenwu Xie, Peng Zhu

“…Comprehensive experimental analyses on established benchmark functions have validated the efficacy of the IGWO-CS method, illustrating its competitiveness with other advanced algorithms such as the Ranking-based Adaptive Cuckoo Search (RACS) and Modified Particle Swarm Optimization (MPSO). …”
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Stackelberg Game Optimization Strategy of Virtual Power Plants and Electric Vehicles Based on Conditional Value-at-Risk by MA Qianxin, JIA Heping, GUO Yuchen, LI Peijun, YANG Ye, LIU Dunnan, ZHAO Zhenyu

“…The lower-level model minimized user costs by responding to these prices using a utility function that captures both cost satisfaction and charging experience. A particle swarm optimization algorithm was employed to solve the coupled model and identify the equilibrium strategies.…”
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Optimization and analysis of interior permanent magnet drive motor with unequal thickness magnetic poles for electric vehicle by Shilun MA, Yongyi WU, Changwei LI, Keqi CHEN

“…Finally, with torque ripple, cogging torque, and output torque as optimization objectives, the particle swarm optimization algorithm was used to perform multi-objective optimization on the maximum magnetic pole thickness, minimum magnetic pole thickness, the width of magnetic pole, the depth and width of the rotor auxiliary slots, in order to determine the optimal parameters, and a prototype was then developed for experimental testing. …”
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Assessment of the Aging State for Transformer Oil-Barrier Insulation by Raman Spectroscopy and Optimized Support Vector Machine by Deliang Liu, Biao Lu, Wenping Wu, Wei Zhou, Wansu Liu, Yiye Sun, Shilong Wu, Guolong Shi, Leiming Yuan

“…The SVM parameters were optimized using grid search, particle swarm optimization (PSO), and genetic algorithm (GA), yielding the optimal parameters (C and gamma). …”
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Improving energy efficiency and routing reliability in wireless sensor networks using modified ant colony optimization by Medhat A. Tawfeek, Ibrahim Alrashdi, Madallah Alruwaili, Leila Jamel, Gamal Farouk Elhady, Haitham Elwahsh

“…We compare the performance of the proposed MACOA with existing state-of-the-art techniques, such as Genetic Algorithms, Particle Swarm Optimization, Artificial Bee Colony, Deep Reinforcement Learning, and Energy Reliable ACO Routing Protocol (E-RARP) in terms of network lifetime, network stabilization time, energy efficiency, load balancing, and throughput. …”
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Performance Optimization Method of Steam Generator Liquid Level Control Based on Hybrid Iterative Model Reconstruction by Xiaoyu Li, Xiangsong Kong, Changqing Shi, Jinguang Shi, Zean Yang

“…The method first constructs the initial dataset with a small-sample Latin-square experiment design and then builds two different fitting models, SVM and Kriging, based on the initial dataset respectively, under the hybrid model fusion idea. After that, the particle swarm optimization algorithm is used to calculate the optimal point of the current valid model, and the optimization process is controlled by establishing the iteration termination judgment based on the historical iteration data. …”
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Integrated optimization and coordination of cascaded reservoir operations: Balancing flood control, sediment transport and ecosystem service by Xinmiao Cao, Teng Lin, Jiahui Li, Ting Zhou

“…To address the optimization model, an elite mutation‐based multi‐objective particle swarm optimization (MOPSO) algorithm that integrates genetic algorithms (GA) is developed. …”
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Failure thresholds and weak part identification in cascade reservoir system: A risk-based optimization framework by Haibin Wang, Jiahong Liu, Chao Mei, Jia Wang, Tianxu Song

“…Secondly, a dynamic Particle Swarm Optimization-Genetic Algorithm (PSO-GA) model optimizes outflow strategies during flood events. …”
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Queen honey bee migration (QHBM) optimization for droop control on DC microgrid under load variation by Aripriharta Aripriharta, Mochammad Syarifudin Al Rasyid, Muhammad Cahyo Bagaskoro, Irham Fadlika, Sujito Sujito, Arif Nur Afandi, Saodah Omar, Norzanah Rosmin

“…The optimizcv ation considers reference voltage constraints and virtual impedance at various load conditions, particularly resistive. The optimization problem is addressed using two techniques: queen honey bee migration (QHBM) and particle swarm optimization (PSO). …”
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Adaptive continuous-discrete variables optimization for active learning with extremely sparse data in optical material design by Serang Jung, Eungkyu Lee

“…In the adaptive scheme, we examine the performance of three machine learning (ML) models—Gaussian process regression, factorization machines (FM), and field-aware FM—for a surrogate function, and ML model-specific optimization algorithms such as discrete particle swarm optimization, artificial bee colony optimization, and simulated annealing. …”
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Optimization of a Coupled Neuron Model Based on Deep Reinforcement Learning and Application of the Model in Bearing Fault Diagnosis by Shan Wang, Jiaxiang Li, Xinsheng Xu, Ruiqi Wu, Yuhang Qiu, Xuwen Chen, Zijian Qiao

“…By comparing the coupled neuron model optimized with a reinforcement learning algorithm, particle swarm algorithm, and quantum particle swarm algorithm, the experimental results show that the coupled neuron model optimized with a deep reinforcement learning algorithm has the optimal signal-to-noise ratio of the output signal and recognition rate of the bearing faults, which are −13.0407 dB and 100%, respectively. …”
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Developing a novel approach for passive damped LCL filter and controller parameter design using PSO algorithm in VSC-based islanded microgrids by Yared Bekele Beyene, Getachew Biru Worku, Lina Bertling Tjernberg

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Adaptive Control Parameter Optimization of Permanent Magnet Synchronous Motors Based on Super-Helical Sliding Mode Control by Lingtao Kong, Hongxin Zhang, Tiezhu Zhang, Junyi Wang, Chaohui Yang, Zhen Zhang

“…The Non-dominated Sorting Genetic Algorithm II and Multi-objective Particle Swarm Optimization are employed to effectively optimize control parameters, thereby mitigating motor torque and speed overshoot. …”
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MbGWO-SFS: Modified Binary Grey Wolf Optimizer Based on Stochastic Fractal Search for Feature Selection by El-Sayed M. El-Kenawy, Marwa Metwally Eid, Mohamed Saber, Abdelhameed Ibrahim

“…The results, compared to binary versions of the-state-of-the-art optimization techniques such as the original GWO, SFS, Particle Swarm Optimization (PSO), hybrid of PSO and GWO, Satin Bowerbird Optimizer (SBO), Whale Optimization Algorithm (WOA), Multiverse Optimization (MVO), Firefly Algorithm (FA), and Genetic Algorithm (GA), show the superiority of the proposed algorithm. …”
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Improvement of the Dynamic Response of Robust Sliding Mode MPPT Controller-Based PSO Algorithm for PV Systems under Fast-Changing Atmospheric Conditions by Dieudonné Marcel Djanssou, Abdouramani Dadjé, Ahmat Tom, Noël Djongyang

“…This paper presents the optimization by the swarm particles (PSO) of a sliding mode controller (SMC) to optimize photovoltaic systems (PV) evolving under the conditions of a rapid variation of the sunshine. …”
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A Bio-Optimization Approach for Renewable Energy Management: The Case of a University Building in a Tropical Climate by Orlando Aguilar Pinzón, Orlando Aguilar Gallardo, Miguel Chen Austin

“…This study presents a theoretical application of bio-inspired algorithms, specifically the Particle Swarm Optimization (PSO) algorithm and the Genetic Algorithm (GA), to enhance the energy availability of a renewable energy system in an existing university building in a tropical climate. …”
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Physics-Informed Neural Network for Load Margin Assessment of Power Systems with Optimal Phasor Measurement Unit Placement by Murilo Eduardo Casteroba Bento

“…Three different metaheuristics called the Hiking Optimization Algorithm, Artificial Protozoa Optimizer, and Particle Swarm Optimization were applied and evaluated in the test system. …”
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Implementation of class topper optimized fractional order proportional-integral-derivative controller for cart-inverted pendulum system by Neelam Verma, Anjali Jain

“…Results indicate that the proposed approach outperforms existing methods such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Ant Colony Optimization (ACO). …”
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Forecasting Daily and Monthly Reference Evapotranspiration in the Aidoghmoush Basin Using Multilayer Perceptron Coupled with Water Wave Optimization by Fatemeh Sayyahi, Saeed Farzin, Hojat Karami

“…The aim of this study is to evaluate the ability of soft computing models including multilayer perceptron- (MLP-) water wave optimization (MLP-WWO), MLP-particle swarm optimization (MLP-PSO), and MLP-genetic algorithm (MLP-GA), to simulate the daily and monthly reference evapotranspiration (ET) at the Aidoghmoush basin (Iran). …”
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