Research into prediction and influential factors of circuit breaker closing time using BFGS-NN by Longcheng Dai, Jiaying Yu, Zhihui Huang, Hui Ni, Yifan Zhang, Junting Dou

“…On-site operational data were analyzed to build a circuit breaker action time database. The BFGS algorithm trained on these data generated a closing time prediction model, achieving rapid convergence and optimal fit during learning. …”
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HiCoACR: A reconfiguration decision-making model for reconfigurable security protocol based on hierarchically collaborative ant colony by Zhuo Yi, Ying Liao, Xuehui Du, Xin Lu, Lifeng Cao

“…The Explorer controls directions of protocol reconfiguration and generates abstract scheduling sub-goals which are conveyed from the Worker. While the Worker schedules most suitable cryptogram resources for each sub-goal received and produces the optimal reconfiguration solution which is verified and re-optimized by a Lévy process–based stochastic gradient descent algorithm. …”
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Task allocation and path planning for multi-robot systems in intelligent warehousing by CHU Jing, TIAN Yiqiu, YUE Qi, HUANG Yong

“…Additionally, a two-layer path planning strategy is proposed: the outer layer conducts global path planning based on the Floyd algorithm, while the inner layer resolves various collision issues through traffic rule constraints, achieving local optimal path planning. …”
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Multivisit Drone-Vehicle Routing Problem with Simultaneous Pickup and Delivery considering No-Fly Zones by Yan-Qiu Liu, Jing Han, Ying Zhang, Yan Li, Tao Jiang

“…Given the intricacy of the MILP model, we propose a two-stage heuristic algorithm based on a simulated annealing approach, combined with strategies for rectifying infeasible solutions and expediting algorithmic processes. …”
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Growth Curve Models and Clustering Techniques for Studying New Sugarcane Hybrids by Carlos David Carretillo Moctezuma, María Guzmán Martínez, Flaviano Godínez-Jaimes, José C. García-Preciado, Ramón Reyes Carreto, José Terrones Salgado, Edgar Pérez Arriaga

“…According to the Connectivity and Dunn indexes, the DBSCAN algorithm provides the best clustering structure for materials in the plant cycle, while for the ratoon cycle, the k-means algorithm offers the best clustering structure. …”
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Designing diverse and high-performance proteins with a large language model in the loop. by Carlos A Gomez-Uribe, Japheth Gado, Meiirbek Islamov

“…We present a protein engineering approach to directed evolution with machine learning that integrates a new semi-supervised neural network fitness prediction model, Seq2Fitness, and an innovative optimization algorithm, biphasic annealing for diverse and adaptive sequence sampling (BADASS) to design sequences. …”
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YOLOv8-OCHD: A Lightweight Wood Surface Defect Detection Method Based on Improved YOLOv8 by Zuxing Chen, Junjie Feng, Xueyan Zhu, Bin Wang

“…This effectively reduces the difficulty and cost of deployment on mobile terminals while significantly improving algorithm accuracy, meeting real-time requirements, and providing a more efficient and feasible technical solution for relevant applications. …”
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Pig Aggression Tracking and Analysis Application Based on A RPMeMOTR Method by Shuqin Tu, Haoxuan Ou, Aqing Yang, Yun Liang, Jiaying Du, Yuefei Cao, Ruilin He, Fang Yuan

“…The management of pig aggression in group-housed environments is crucial for ensuring animal welfare and optimizing production efficiency in the global agricultural industry. …”
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In situ fully vectorial tomography and pupil function retrieval of tightly focused fields by Xin Liu, Shijie Tu, Yiwen Hu, Yifan Peng, Yubing Han, Cuifang Kuang, Xu Liu, Xiang Hao

“…When combined with our decoding algorithm, this strategy mitigates the imperfections in the detection path. …”
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Balancing resource utilization and slice dissatisfaction through dynamic soft slicing for 6G wireless networks by Zeinab Sasan, Siavash Khorsandi

“…The problem is formulated as a Mixed Integer Linear Programming (MILP) model, aiming to maximize network utilization while minimizing slice dissatisfaction. Given the NP-hard nature of the problem, we propose the Heuristic Resource Allocation for Soft Slicing (HRASS) algorithm, which achieves near-optimal performance with significantly reduced computational complexity. …”
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Cascade-Based Input-Doubling Classifier for Predicting Survival in Allogeneic Bone Marrow Transplants: Small Data Case by Ivan Izonin, Roman Tkachenko, Nazarii Hovdysh, Oleh Berezsky, Kyrylo Yemets, Ivan Tsmots

“…The proposed method was tested on a small dataset within transplantology, focusing on binary classification. Optimal parameters for the method were identified using the Dual Annealing algorithm. …”
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Impedance-Driven Decoupling Water–Nitrogen Stress in Wheat: A Parallel Machine Learning Framework Leveraging Leaf Electrophysiology by Shuang Zhang, Xintong Du, Bo Zhang, Yanyou Wu, Xinyi Yang, Xinkang Hu, Chundu Wu

“…A parallel modelling strategy was implemented employing Gradient Boosting, Random Forest, and Ridge Regression, selecting the optimal algorithm per feature based on predictive performance. …”
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Remote Target High-Precision Global Geolocalization of UAV Based on Multimodal Visual Servo by Xuyang Zhou, Ruofei He, Wei Jia, Hongjuan Liu, Yuanchao Ma, Wei Sun

“…We design a step-convergent target geolocation optimization algorithm. By adjusting the step size and the scale factor of the cost function, we achieve fast accuracy convergence for different UAV reconnaissance modes, while maintaining the geolocation accuracy without divergence even when the laser ranging sensor is turned off for a short period. …”
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On-Board Content Caching With Dynamic Cache Reconfiguration in Multi-Layer Satellite Edge Networks by Haftay Gebreslasie Abreha, Ilora Maity, Houcine Chougrani, Christos Politis, Symeon Chatzinotas

“…To address these challenges, in this paper, we propose an on-board dynamic cache reconfiguration strategy that maximizes the cache hit rate while minimizing reconfiguration overhead. We design a proximity-based content popularity model and an Age of Information (AoI)-aware caching strategy to optimize on-board satellite resources, enhancing the cache hit rate and ensuring content freshness. …”
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XSQ-Learning: Adaptive Similarity Thresholds for Accelerated and Stable Q-Learning by Ansel Y. Rodríguez González, Roberto E. López Díaz, Shender M. Ávila Sansores, María G. Sánchez Cervantes

“…Reinforcement Learning (RL) enables agents to learn optimal policies through environment interaction, with Q-learning being a fundamental algorithm for Markov Decision Processes (MDPs). …”
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Lightweight UAV Detection Method Based on IASL-YOLO by Huaiyu Yang, Bo Liang, Song Feng, Ji Jiang, Ao Fang, Chunyun Li

“…To address this, we propose the IASL-YOLO algorithm, which optimizes the YOLOv8s model to enhance detection accuracy and lightweight efficiency. …”
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Heterogeneity-aware device selection for efficient federated edge learning by Yiran Shi, Jieyan Nie, Xingwei Li, Hui Li

“…To address these issues, this paper proposes a novel Quality-aware online Device Selection (QDS) algorithm. The QDS algorithm leverages a greedy selection method that guarantees the deadline restrictions and reflects upon their historical performance metrics, as indicated by their loss function values from preceding training rounds. …”
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Pseudolite Self-Interference Cancellation Without Additional GNSS Signal Distortion by Lichao Gao, Jin He, Yuanxin Wu, Wenxian Yu

“…The simulation test results show that the algorithm can filter self-interference without additional distortion of the satellite navigation signals. …”
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Mapping the landscape of machine learning in chronic disease management: A comprehensive bibliometric study by Shiying Shen, Wenhao Qi, Sixie Li, Jianwen Zeng, Xin Liu, Xiaohong Zhu, Chaoqun Dong, Bin Wang, Qian Xu, Shihua Cao

“…Logistic regression (n = 459) remains the most widely used algorithm, while neural networks (n = 183) show promising potential. …”
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A YOLOv8n-T and ByteTrack-Based Dual-Area Tracking and Counting Method for Cucumber Flowers by Liyang Su, Shujuan Zhang, Hongtu Zhang, Xiangsen Meng, Xiongkui He

“…The YOLOv8n-T incorporates a Coordinate Attention (CA) mechanism and lightweight modules while optimizing the loss function, thereby improving floral feature extraction capabilities and reducing computational complexity. …”
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