Addressing model errors in UAV altitude control using compensator by Gilang Nugraha Putu Pratama, Alfian Maarif, Iswanto Iswanto, Evi Wahyu Pratiwi

“…This study proposes a model error compensator designed to mitigate errors arising from parametric uncertainties using the Particle Swarm Optimization (PSO) algorithm. Simulation results confirm that the proposed compensator effectively reduces response variations caused by uncertainties and time delays, demonstrating its potential to enhance the reliability of altitude control in UAV quadrotors.…”
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Genetical Swarm Optimization of Multihop Routes in Wireless Sensor Networks by Davide Caputo, Francesco Grimaccia, Marco Mussetta, Riccardo E. Zich

“…In order to maximize the network lifespan, in this paper, genetical swarm optimization (GSO) is applied, a class of hybrid evolutionary techniques developed in order to exploit in the most effective way the uniqueness and peculiarities of two classical optimization approaches; particle swarm optimization (PSO) and genetic algorithms (GA). …”
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Resilience-Improving Based Optimization of Post-Disaster Emergency Maintenance Strategy for Transmission Networks by Haiping LIANG, Haoyan SHI, Yan WANG, Yingpei LIU, Xinming WANG

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Midspan Deflection Prediction of Long-Span Cable-Stayed Bridge Based on DIWPSO-SVM Algorithm by Lilin Li, Qing He, Hua Wang, Wensheng Wang

“…This study proposes a novel hybrid model, DIWPSO-SVM, which integrates dynamic inertia weight particle swarm optimization (DIWPSO) with support vector machines (SVMs) to enhance the prediction accuracy of midspan deflection. …”
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Comparative Study of White Shark Optimization and Combined Meta-Heuristic Algorithm for Enhanced MPPT in Photovoltaic Systems by Fajar Kurnia Al Farisi, Zhi-Kai Fan, Kuo-Lung Lian

“…This paper proposes a novel hybrid metaheuristic algorithm (MHA) for maximum power point tracking (MPPT), integrating particle swarm optimization (PSO), the differential evolution algorithm (DEA), and the grey wolf optimizer (GWO). …”
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Comparison of Maximum Power Point Tracking Methods Using Metaheuristic Optimization Algorithms for Photovoltaic Systems by Necati Bilgin, İrfan Yazici

“…In the simulation studies, the output powers obtained by the application of particle swarm optimization, cuckoo optimization, bat optimization and firefly optimization techniques as MPPT algorithm has been compared. …”
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A genetic programming-based ensemble method for long-term electricity demand forecasting by Hayat Ahmed Issa, Hasan Hüseyin Çevik, Ahmet Yilmaz, Mehmet Cunkas

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Two-Stage Uncertain UAV Combat Mission Assignment Problem Based on Uncertainty Theory by Haitao Zhong, Rennong Yang, Aoyu Zheng, Mingfa Zheng, Yu Mei

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A new method for recognizing geometric parameters of industrial robots by Bin Kou, Yi Zhang

“…Following this, we improve the accuracy of global optimization of the particle swarm optimization (PSO) algorithm by drawing on the wandering behavior of the wolf pack algorithm and hybridization behavior of the genetic algorithm. …”
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Hybrid precoding method for millimeter-wave massive MIMO systems based on IAFS algorithm by Haoyi CHEN, Guangqiu LI, Hui LI

“…The millimeter-wave massive multiple-input multiple-output (MIMO) systems can overcome the adverse effects of the free-space signal path loss through the partial connection hybrid precoding method, which has the advantages of low hardware complexity and high energy efficiency.When the number of input data streams is equal to the number of radio frequency (RF) links, the hybrid precoding method based on partially connected structure and serial interference cancellation can be used.When the number of input data streams is not equal to the number of RF links, a hybrid precoding method based on improved artificial fish swarm (IAFS) algorithm was proposed.The core idea is that based on the spectral efficiency optimization criteria and the characteristics of partial connected structure, the spectral efficiency optimization problem of analog recoding matrix variables was transformed into the spectral efficiency optimization problem based on vector variables, and then the IAFS algorithm was used to solve the spectrum efficiency optimization problem.The simulation results show that the proposed method has good spectral efficiency and energy efficiency under the condition of low signal-to-noise ratio, and is expected to be applied in the real scene.…”
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Wireless sensor node localization based on IPSO-MC by Yongyan LI, Jianping WU

“…To solve the problem of insufficient node positioning accuracy in wireless sensor networks,an algorithm based on improved particle swarm optimization by membrane computing (IPSO-MC) was proposed.Kent mapping was used to initialize the population and domain particles were introduced to improve the global optimization of the particle swarm.The weight factor and nonlinear extreme value perturbation were used to improve the local optimization ability of the particle swarm,and the Levy flight mechanism was used to optimize the individual position.Finally,the optimal solution of the particle swarm algorithm was obtained by the evolutionary rules of the membrane computing.Simulation experiments show that compared with the chicken flock algorithm,the improved particle swarm algorithm and the membrane computing,the proposed algorithm improves 3.24%,5.12% and 8.15% in the comparison of reference node ratio indicators,and the increase in the number of nodes indicators by 2.26%,7.82% and 9.81%,and the comparison of communication radius indicators increased by 2.15%,5.5% and 7.5%,respectively.This indicates that the algorithm has a good effect in node localization.…”
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Parameter Optimization Design of Light induction Power-taking Device for Transmission Cable by LIN Jin-shu, ZHOU Mao-xi, CHEN Dao-mo, WANG Lu-yang, SUI Li-cheng

“…Increased stress and longterm operation will endanger the safety of the power system Therefore, based on the premise of reducing the weight of the magnetic core, this paper adopts the particle swarm algorithm to globally optimize the magnetic core size, air gap size and the number of turns of the coil. …”
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Multi-objective operation optimization method of microgrid considering the influence of electric vehicle by Tiefeng Xu, Xiaofang Meng, Fangfang Zheng, Yiduo Zhang, Xin Wu, Mingyang Li

“…Taking the minimum total operating cost and the minimum peak-valley difference of the microgrid in one day as the optimization objective, and considering many constraints such as power balance constraints and output constraints of distributed generation units, the multi-objective optimization function is transformed into a single-objective optimization function by linear weighting method, and the model is solved by particle swarm optimization algorithm. …”
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Sensor Node Deployment Optimization for Continuous Coverage in WSNs by Haris Muhammad, Haewoon Nam

“…To address these issues, this paper presents a novel velocity-scaled adaptive search factor particle swarm optimization (VASF-PSO) algorithm that integrates dynamic mechanisms to enhance population diversity, guide the search process more effectively, and reduce uncovered areas. …”
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Orthogonal Multi‐Swarm Greedy Selection Based Sine Cosine Algorithm for Optimal FACTS Placement in Uncertain Wind Integrated Scenario Based Power Systems by Sunilkumar P. Agrawal, Pradeep Jangir, Arpita, Sundaram B. Pandya, Anil Parmar, Mohammad Khishe, Bhargavi Indrajit Trivedi

“…Flexible AC Transmission System (FACTS) devices, including Static VAR Compensator (SVC), Thyristor‐Controlled Series Compensator (TCSC), and Thyristor‐Controlled Phase Shifter (TCPS), enhance system stability, reduce losses, and lower operational costs when optimally placed. Conventional optimization techniques like Particle Swarm Optimization (PSO), Sine Cosine Algorithm (SCA), Moth Flame Optimization (MFO), Gray Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA) struggle to balance exploration and exploitation in complex OPF problems, leading to suboptimal solutions. …”
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Deephive: A Reinforcement Learning Approach for Automated Discovery of Swarm-Based Optimization Policies by Eloghosa Ikponmwoba, Opeoluwa Owoyele

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Viewpoint Selection for 3D Scenes in Map Narratives by Shichuan Liu, Yong Wang, Qing Tang, Yaoyao Han

“…Pearson’s correlation coefficient is used to evaluate the relationship between visual salience and narrative relevance, serving as a constraint to construct a viewpoint fitness function that integrates the visual salience of the convex polyhedron enclosing the scene. The chaotic particle swarm optimization (CPSO) algorithm is utilized to locate the viewpoint position while maximizing the fitness function, identifying a viewpoint meeting narrative and visual salience requirements. …”
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A wireless sensor data-based coal mine gas monitoring algorithm with least squares support vector machines optimized by swarm intelligence techniques by Peng Chen, Yonghong Xie, Pei Jin, Dezheng Zhang

“…Due to the fact that the “negative samples” of coal mine safety data are scarce, least squares support vector machine is introduced to deal with this problem. In addition, several swarm intelligence techniques such as particle swarm optimization, artificial bee colony algorithm, and genetic algorithm are applied to optimize the hyper parameters of least squares support vector machine. …”
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Disturbance Observer-Based Bio-Inspired LQR Optimization for DC Motor Speed Control by Mubarak Badamasi Aremu, Mohammed Abdel-Nasser, Nezar M. Alyazidi, and Sami El-Ferik

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An improved salp swarm algorithm for permutation flow shop vehicle routing problem by Yanguang Cai, Huajun Chen

“…Simulation results show that compared with simulated annealing, genetic algorithm and particle swarm optimization algorithm, the proposed algorithm has better optimization ability. …”
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