Heterogeneous Multi-Agent Deep Reinforcement Learning for Cluster-Based Spectrum Sharing in UAV Swarms by Xiaomin Liao, Yulai Wang, Yang Han, You Li, Chushan Lin, Xuan Zhu

“…Adequate experimental evidence has confirmed that the HMDRL-UC algorithm proposed in this paper is not only capable of managing dynamic drone swarm scenarios in the presence of partial CDI, but also has a clear advantage over the other existing three algorithms in terms of average throughput, intra-cluster communication delay, and minimum signal-to-noise ratio (SNR).…”
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Information Bottleneck-Based Domain Adaptation for Hybrid Deep Learning in Scalable Network Slicing by Tianlun Hu, Qi Liao, Qiang Liu, Georg Carle

“…In this paper, we propose a novel hybrid deep learning algorithm called IDLA (integrated deep learning with the Lagrangian method). …”
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Fault Location and Route Selection Strategy of Distribution Network Based on Distributed Sensing Configuration and Fuzzy C-Means by Bo Li, Guochao Qian, Lijun Tang, Peng Sun, Zhensheng Wu

“…The results show that, compared with the traditional fault section location and route selection strategy, this method can reduce the number of measurement devices optimally configured by 19–36% and significantly reduce the number of algorithm iterations. In addition, it can realize rapid fault location and precise line screening at a low equipment cost under multiple fault types and different fault locations, which significantly improves fault location accuracy while reducing economic investment.…”
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New contextual collaborative filtering system with application to personalized healthy nutrition education by Hanane Zitouni, Souham Meshoul, Chaker Mezioud

“…The middle layer is based on a collaborative filtering algorithm that takes into account the users’ preferences, interests and priorities; while the deepest layer, which is considered the most relevant in our multilayer architecture, focuses on a post-filtering algorithm in which the recommendations are much more adapted to the user environment. …”
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Fast Low Rank and Sparse Decomposition Based on Greedy Bilateral Smoothing for Infrared Small Target Detection by Yan-Shan Zhang, Ze-Yin Li, Dong-Dong Pang, Lu-Yao Wang, Cheng-Jun Wu, Kang Duan, Jun-Ming Gao

“…Specifically, in order to improve optimization efficiency, greedy bilateral smoothing is employed to model low rank backgrounds, resulting in a significant improvement in the efficiency of the detection algorithm. Then, a optimization algorithm framework based on alternating projection is designed to achieve an accurate separation of target and background. …”
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Optimized dual NURBS curve interpolation for high-accuracy five-axis CNC path planning by Yi Xu, Mohd Hairi Mohd Zaman, Feng Zhou

“…This study presents a dual NURBS curve interpolation algorithm specifically designed for five-axis synchronized motion. …”
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Basis Recovery Method for Ionospheric Delay Corrections in PPP-RTK Model with Recommendations for Interpolation Reference Station Number Selection by Siyao Wang, Runzhi Zhang, Rui Tu, Lihong Fan, Xiaochun Lu

“…Furthermore, approximately 3% of the observations, which would otherwise have been discarded due to the missing corrections from a specific reference station, are retained by the algorithm.…”
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Implementation of SMOTE to Improve the Performance of Random Forest Classification in Credit Risk Assessment in Banking by Nafa Nur Adifia Nanda, Yuniar Farida, Wika Dianita Utami

“…The precision value rose from 90.83% to 97.03%, while the recall value increased from 60.26% to 91.55%. …”
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Task Allocation and Path Planning Method for Unmanned Underwater Vehicles by Feng Liu, Wei Xu, Zhiwen Feng, Changdong Yu, Xiao Liang, Qun Su, Jian Gao

“…Second, an improved RRT* algorithm termed GR-RRT* is employed for UUV path planning. …”
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Efficient collision-avoidance navigation strategy for autonomous surface vehicles in unstructured and constricted marine environments by Wenlong Meng, Rongdian Ku, Yanbo Pu, Xiaoxiao Shi, Ya Gong

“…Current path planning algorithms designed for unstructured environments, particularly those characterized by narrow spaces, often face difficulties in efficiently exploring the target area while producing high-quality paths. …”
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Analysis of Unmanned Surface Vehicles Heading KF-Based PI-(1+PI) Controller Using Improved Spider Wasp Optimizer by Xiaoyu Li, Xiangye Zeng, Jingyi Wang, Qi Li, Baoshuo Fan, Qi Zeng

“…Traditional PID controllers struggle with nonlinearities and noise in USV systems while existing metaheuristic algorithms face limitations in balancing exploration and exploitation. …”
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Calibration Transfer of Soil Total Carbon and Total Nitrogen between Two Different Types of Soils Based on Visible-Near-Infrared Reflectance Spectroscopy by Xue-Ying Li, Yan Liu, Mei-Rong Lv, Yan Zou, Ping-Ping Fan

“…The former could only be used for correction among instruments, while the latter fundamentally solved the problem of model sharing across different samples.…”
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Three-dimensional reconstruction and structural surface identification of high steep slopes based on UAV close-range photogrammetry by Linfeng WANG, Hui JIANG, Ning TANG, Xiaoming HUANG, Guojin TAN

“…An adaptive KNN algorithm is introduced to enhance the coplanarity detection passing rate in point clouds, while optimal planar equations are fitted using the least squares method. …”
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Optimizing ensemble learning for satellite-based multi-hazard monitoring and susceptibility assessment of landslides, land subsidence, floods, and wildfires by Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi-Niaraki, Farman Ali, Biswajeet Pradhan, Soo-Mi Choi

“…To address this gap, this study uses two meta-heuristic algorithms (Genetic Algorithm (GA) and Particle Swarm Optimization (PSO)) to provide an optimized Random Forest (RF) model with better predictive ability. …”
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A Hardware Accelerator for Real-Time Processing Platforms Used in Synthetic Aperture Radar Target Detection Tasks by Yue Zhang, Yunshan Tang, Yue Cao, Zhongjun Yu

“…The deep learning object detection algorithm has been widely applied in the field of synthetic aperture radar (SAR). …”
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Integration of Distributed Energy Resources in Unbalanced Networks Using a Generalized Normal Distribution Optimizer by Laura Sofía Avellaneda-Gómez, Brandon Cortés-Caicedo, Oscar Danilo Montoya, Jesús M. López-Lezama

“…A leader–followeroptimization framework is adopted, where the leader stage utilizes the Generalized Normal Distribution Optimization (GNDO) algorithm to generate candidate solutions, while the follower stage conducts power flow calculations through successive approximation to assess the objective value. …”
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Damage Identification of Railway Bridge KW51 Conditions Using Deep-Learning-Based 1D CNN Model by Ali Al-Ghalib, Sawsan Mahmoud

“…This paper compares the damage identification outcomes of the Machine Learning (ML) and Deep Learning (DL) algorithms. The algorithms in both approaches have employed vibration data from the benchmark railway bridge KW51. …”
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ADMM-TransNet: ADMM-Based Sparse-View CT Reconstruction Method Combining Convolution and Transformer Network by Sukai Wang, Xueqin Sun, Yu Li, Zhiqing Wei, Lina Guo, Yihong Li, Ping Chen, Xuan Li

“…Compared with other deep learning algorithms, the proposed algorithm has better generalization and higher reconstruction accuracy.…”
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Novel hybrid arithmetic-equilibrium optimizer as robust tuner for power system stabilizer (PSS) parameters in interconnected electrical power system by Imam Robandi, Mohamad Almas Prakasa, Muhammad Ruswandi Djalal, Shigemasa Takai, Arimbi Kumala Sari, Mochammad Adri Satria Musti

“…A wider-distributed optimal solution and better convergence are also offered by the proposed algorithm. Besides that, the application in the optimal tuning shows that the proposed algorithm can provide the best PSS parameters in different objective functions with better average and standard deviation values. …”
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Robust Beamforming for Superdirective Antenna Arrays and Experimental Validations by Mengying Gao, Haifan Yin, Liangcheng Han, Jingcheng Xie

“…Numerical and electromagnetic (EM) simulations verify the effectiveness of the DoS and the OC-QCLS algorithm. The improvement in communication performance achieved by the OC-QCLS algorithm is demonstrated through its superior average spectral efficiency. …”
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