Finite-Time Control for Satellite Formation Reconfiguration and Maintenance in LEO: A Nonlinear Lyapunov-Based SDDRE Approach by Majid Bakhtiari, Amirhossein Panahyazdan, Ehsan Abbasali

“…This optimization process minimizes energy usage through a hybrid genetic algorithm and simulated annealing (HGASA), resulting in improved performance. …”
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Design and Experiment of a Greenhouse Autonomous Following Robot Based on LQR–Pure Pursuit by Yibin Hu, Jieyu Xian, Maohua Xiao, Qianzhe Cheng, Tai Chen, Yejun Zhu, Guosheng Geng

“…These findings confirm that the designed robot can sustain its payload under most operating scenarios and that the proposed tracking strategy effectively suppresses deviations and improves path-following accuracy.…”
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An Experimental Comparison of Self-Adaptive Differential Evolution Algorithms to Induce Oblique Decision Trees by Rafael Rivera-López, Efrén Mezura-Montes, Juana Canul-Reich, Marco-Antonio Cruz-Chávez

“…This study addresses the challenge of generating accurate and compact oblique decision trees using self-adaptive differential evolution algorithms. Although traditional decision tree induction methods create explainable models, they often fail to achieve optimal classification accuracy. …”
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Algorithms for Load Balancing in Next-Generation Mobile Networks: A Systematic Literature Review by Juan Ochoa-Aldeán, Carlos Silva-Cárdenas, Renato Torres, Jorge Ivan Gonzalez, Sergio Fortes

“…The need for enhanced radio resource allocation schemes, improved user mobility and increased throughput, driven by a rising demand for data, has necessitated the development of diverse algorithms that optimize output values based on varied input parameters. …”
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Flexible Adaptive Marine Predator Algorithm and Its Application in Fault Detection for Wind Turbines by WANG Wen, YI Jiabiao

“…FAMPA allows for flexibly adjusting population location changes to optimize the balance between global exploration and local exploitation, thus significantly improving both convergence rates and optimization accuracy. …”
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Efficient Pathfinding on Grid Maps: Comparative Analysis of Classical Algorithms and Incremental Line Search by Amr Elshahed, Majid Khan Bin Majahar Ali, Ahmad Sufril Azlan Mohamed, Farah Aini Binti Abdullah, Ts. Lee Jian Aun

“…Pathfinding on grid maps is a cornerstone problem in robotics, autonomous navigation, and game development. Classical algorithms such as A*, Dijkstra’s, and Breadth-First Search (BFS) are known for their ability to guarantee optimal solutions, while others like Depth-First Search (DFS) and Greedy Best-First Search prioritize speed over optimality. …”
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An approach based on genetic algorithms and neural networks for QoS-aware IoT services composition by Rabah Boucetti, Ouassila Hioual, Sofiane Mounine Hemam

“…Finally, we apply the second GA on the concrete services of the retained categories, in order to obtain the IoT service concrete composition with an overall QoS optimization. The simulation results show that the proposed approach has the best composition time, the best Hypervolume indicator and the best compositional optimality compared to SC-FLA, Improved GA and MGA approaches. …”
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An Enhanced Forwarding Method based on Intelligent Water Drops Algorithm in Named Data Network by HamidReza Afzal, Behrang Barekatain, Zahra Beheshti

“…Although Named Data Network (NDN) has made a bright future in Internet for high volume of requests by many users, how to send a request package (I-Pkt) consciously from the consumer to the Producer and returning the data package (D-Pkt) inversely is still one of its most important challenges. According to the recent limited researches, using service quality parameters beside an optimization algorithm like ant colony to find the optimal path has been an appropriate response to solve this problem. …”
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Dynamic scheduling for flexible job shop based on MachineRank algorithm and reinforcement learning by Fujie Ren, Haibin Liu

“…To improve the quality of the model solutions, a MachineRank algorithm (MR) is proposed, and based on the MR algorithm, seven composite scheduling rules are introduced. …”
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Identifying Capsule Defect Based on an Improved Convolutional Neural Network by Junlin Zhou, Jiao He, Guoli Li, Yongbin Liu

“…The improved CNN algorithm is based on regularization and the Adam optimizer (RACNN), on which a dropout layer and L2_regularization are added between the full connection and the output layer to solve the overfitting problem. …”
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First aid for generalized seizures: modern approaches and opportunities for improvement by А. А. Birkun, L. I. Dezhurny

“…Since immediate arrival of emergency medical service (EMS) specialists to a victim is impossible in most cases, first aid (FA) provision by immediate witnesses of seizures is of paramount importance for preventing death.Objective: to analyze modern principles and approaches to FA provision for generalized seizures, to study existing organizational framework and to identify areas for improving the organization of FA provision for seizures, as well as to develop a draft domestic algorithm for distant consultation of untrained witnesses by emergency dispatchers on FA provision in generalized seizures.Material and methods. …”
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Predictive modelling of aquaculture water quality using IoT and advanced machine learning algorithms by Md. Abdullah Al Mamun Hridoy, Chiara Bordin, Andleeb Masood, Khalid Masood

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Local Outlier Detection Method Based on Improved K-means by Yu ZHOU, Hao XIA, Xuezhen YUE, Peichong WANG

“…Hence, an improved K-means clustering algorithm is proposed by introducing fast search and discovering density peak methods. …”
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Third or fourth branchial pouch sinus lesions: a case series and management algorithm by Yun Li, Kexing Lyu, Yihui Wen, Yang Xu, Fanqin Wei, Haocheng Tang, Siyu Chen, Zhangfeng Wang, Xiaolin Zhu, Weiping Wen, Wenbin Lei

“…Conclusion Refining fistula subtypes and adopting corresponding treatment measures can reduce the recurrence rate and improve curative effects. We propose and advocate this treatment algorithm for all third and fourth branchial pouch lesions.…”
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An optimization-inspired intrusion detection model for software-defined networking by Hui Xu, Longtan Bai, Wei Huang

“…The experimental results show that the ESWO-IDM achieves the best performance in all the metrics in both binary classification and multiclassification and has the most prominent effect on the detection of normal, denial of service (DoS), distributed DoS, and Brute Force Attack types, which effectively improves SDN intrusion detection from the viewpoint of optimization.…”
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Predicting the Likelihood of Operational Risk Occurrence in the Banking Industry Using Machine Learning Algorithms by Hamed Naderi, Mohammad Ali Rastegar Sorkhe, Bakhtiar Ostadi, Mehrdad Kargari

“…Specifically, the RF algorithm achieved an accuracy of 0.9690, while the SVM algorithm attained an accuracy of 0.9587 in State 1, making them the most effective models in this setting. …”
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Private Stochastic Optimization with Large Worst-Case Lipschitz Parameter by Andrew Lowy, Meisam Razaviyayn

“…To do so, we develop novel algorithmic and stability-based proof techniques, which we believe will be useful for future work in obtaining optimal excess risk. …”
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Two-Dimensional Beam Selection by Multiarmed Bandit Algorithm Based on a Quantum Walk by Maki Arai, Tomoki Yamagami, Takatomo Mihana, Ryoichi Horisaki, Mikio Hasegawa

“…This article proposes a novel beam selection method using a multiarmed bandit (MAB) algorithm based on a quantum walk (QW) principle, aimed at improving system performance. …”
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A Cellular Automata-Based Crossover Operator for Binary Chromosome Population Genetic Algorithms by Doru Constantin, Costel Bălcău

“…After presenting the fundamental elements regarding cellular automata with specific examples for one- and two- dimensional cases, the the most widely used crossover operators in applications with genetic algorithms are described, and the crossover operator based on cellular automata is defined. …”
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Deep Learning-Based Feature Matching Algorithm for Multi-Beam and Side-Scan Images by Yu Fu, Xiaowen Luo, Xiaoming Qin, Hongyang Wan, Jiaxin Cui, Zepeng Huang

“…It also overcomes challenges, such as large nonlinear differences, significant geometric distortions, and high matching difficulty between the MBES and side-scan images, significantly improving the optimized image matching results. The matching error RMSE has been reduced to within six pixels, enabling the accurate matching of multi-beam and side-scan images.…”
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