Formation Flight of Fixed-Wing UAVs: Dynamic Modeling, Guidance Design, and Testing in Realistic Scenarios by Carlo E.D. Riboldi, Marco Tomasoni

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Enhancing Power Quality in Grid-Integrated Hybrid Renewable Energy System using ANFIS-FBSO by Singh Manpreet, Singh Lakhwinder

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Research on Fire Detection of Cotton Picker Based on Improved Algorithm by Zhai Shi, Fangwei Wu, Changjie Han, Dongdong Song

“…Therefore, in this study, we designed an improved algorithm for multi-sensor data fusion; built a cotton picker fire detection system by using infrared temperature sensors, CO sensors, and the upper computer; and proposed a BP neural network model based on improved mutation operator hybrid gray wolf optimizer and particle swarm optimization (MGWO-PSO) algorithm based on the BP neural network model. …”
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Comprehensive Research on Energy Saving Synergy Optimization and Optimal Real-time Control of Hybrid Electric Mining Trucks by Li Hongliang, Zhang Guojing, Fan Ping

“…This study takes the hybrid electric mining truck as a research object, establishes the mathematical model of the whole vehicle, takes reducing fuel consumption as the goal, establishes a collaborative optimization model that comprehensively considers the interaction between transmission system parameters and energy management strategies, and combines particle swarm optimization (PSO) algorithm and dynamic programming (DP) algorithm to build a two-layer interactive optimization algorithm to eliminate the interaction between transmission system parameters and energy management strategies. …”
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A Deep Neural Network Framework for Dynamic Two-Handed Indian Sign Language Recognition in Hearing and Speech-Impaired Communities by Vaidhya Govindharajalu Kaliyaperumal, Paavai Anand Gopalan

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A Bi-Layer Collaborative Planning Framework for Multi-UAV Delivery Tasks in Multi-Depot Urban Logistics by Junfu Wen, Fei Wang, Yebo Su

“…The lower layer addresses the path planning problem by establishing a multi-objective model that considers path length, flight risk, and altitude variation. An improved particle swarm optimization (PSO) algorithm is proposed by integrating chaotic initialization, linearly adjusted acceleration coefficients and maximum velocity, a stochastic disturbance-based position update mechanism, and an adaptively tuned inertia weight to enhance algorithmic performance and path generation quality. …”
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Water Quality Prediction Based on Hybrid Deep Learning Algorithm by Bhagavathi Perumal, Niveditha Rajarethinam, Anusuya Devi Velusamy, Venkatesa Prabhu Sundramurthy

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Transactive energy management for efficient scheduling and storage utilization in a grid-connected renewable energy-based microgrid by Peter Anuoluwapo Gbadega, Olufunke Abolaji Balogun

“…Comparative analysis reveals that SMA consistently outperforms conventional methods such as Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) in terms of convergence speed and computational efficiency, making it particularly suitable for real-time energy management. …”
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Combining Parallel Stochastic Methods and Mixed Termination Rules in Optimization by Vasileios Charilogis, Ioannis G. Tsoulos, Anna Maria Gianni

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AGC Including ELD and Emission Coordination Using Sine Cosine Algorithm by Ahmed Oday Oleiwi, Ahmed Jasim Sultan

“…The Particle Swarm Optimization (PSO) and Sine Cosine Algorithm (SCA) are used to tune gains of the integral (I) controller to show the superiority in identifying robust controller. …”
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Multijunction solar cell parameter estimation based on metaheuristic algorithms by Marwa M. Elzalabani, Doaa M. Atia, Aref Y. Eliwa, Belal A. Abou Zalam, Mahmoud S. AbouOmar

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Advancing multi-categorization and segmentation in brain tumors using novel efficient deep learning approaches by Nadenlla RajamohanReddy, G. Muneeswari

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A Golden Jackal based optimal operation and optimization of a virtual power plant involving renewable resources by Anubhav Kumar Pandey, Chaima Mansour, Nandini K. K., Vinay Kumar Jadoun, Jayalakshmi N. S.

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Planning trajectory for UAVs using the self-organizing migrating algorithm. by Quoc Bao Diep, Thanh-Cong Truong, Ivan Zelinka

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Detecting Floating-Point Expression Errors Based Improved PSO Algorithm by Hongru Yang, Jinchen Xu, Jiangwei Hao, Zuoyan Zhang, Bei Zhou

“…This paper proposes characteristic particle swarm optimization (CPSO) algorithm based on particle swarm optimization (PSO) algorithm. …”
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Improving Earth surface temperature forecasting through the optimization of deep learning hyper-parameters using Barnacles Mating Optimizer by Zuriani Mustaffa, Mohd Herwan Sulaiman, Muhammad ‘Arif Mohamad

“…The forecasting model is trained on a global temperature dataset with seven inputs and compared with DL models optimized by Particle Swarm Optimization (PSO), Harmony Search Algorithm (HSA), and Ant Colony Optimization (ACO). …”
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A Clustering Approach Using Cooperative Artificial Bee Colony Algorithm by Wenping Zou, Yunlong Zhu, Hanning Chen, Xin Sui

“…In this work, first the CABC algorithm is used for optimizing six widely used benchmark functions and the comparative results produced by ABC, Particle Swarm Optimization (PSO), and its cooperative version (CPSO) are studied. …”
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Photovoltaic Global Maximum Power Tracking Based on Improved Dragonfly Algorithm by Fei XUE, Xin MA, Bei TIAN, Hui WU

“…Finally, comparisons with the P & O algorithm, particle swarm optimization (PSO) algorithm, and the original DA through simulation verify the validity of the proposed algorithm.…”
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Optimal sizing and siting of energy storage systems based on power grid vulnerability analysis: a trilevel optimization model by Zhenghui Zhao, Yingying Shang, Buyang Qi, Yang Wang, Qian Zhang

“…The middle-level employs an improved particle swarm optimization algorithm to determine the optimal capacity and power configuration of BESS, aiming to maximize its equivalent annual revenue. …”
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Adaptive Differential Evolution Algorithm for Forward Position Solution of Parallel Mechanism by Yi Jian

“…Furthermore,the ADE algorithm is compared with basic DE,the adaptive mutation particle swarm optimization,and improved artificial bee colony algorithms,and it is verified that the former outperforms the compared algorithms in term of convergence precision and calculated robustness.…”
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