Three-Dimensional Path Planning of AUVs in Dynamic Obstacle Environments by Chaoyang CHEN, Yute TANG, Yi HUANG, Zhiqun LIU

“…Moreover, dynamic obstacle trajectories were modeled, and the Singer model, combined with the Kalman filter algorithm, was used to precisely predict obstacle states, thereby enhancing the dynamic obstacle avoidance capabilities of AUVs. …”
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Entropy-driven multi agent deep reinforcement learning for resilient distribution networks: coordinating MESS and microgrids by Changchun Cai, Fenglu Gan, Yong Cui, Bo Li, Shixi Hou

“…First, with critical load restoration as the objective function, coordinated optimization model for MESS dispatch and network reconfiguration is constructed, which comprehensively considers security constraints of both distribution networks and microgrids. …”
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Vehicle Trajectory Reconstruction on Urban Traffic Network Using Automatic License Plate Recognition Data by Xinyi Qi, Yanjie Ji, Wenhao Li, Shuichao Zhang

“…Then, candidate trajectories are generated by an improved K-shortest-path (KSP) algorithm based on space-time prism theory. …”
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Control Strategy for PHEB Based on Actual Driving Cycle with Driving Style Characteristic by Jianping Gao, Zhenhai Xu, Xiaojie Gao

“…Based on the 6 driving cycles, the key parameters of rule-based control strategy are optimized and established by a combinatorial optimization algorithm in Isight. …”
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Phase diagram from nonlinear interaction between superconducting order and density: toward data-based holographic superconductor by Sejin Kim, Kyung Kiu Kim, Yunseok Seo

“…We introduce positional embedding layers to improve the learning process in our algorithm, and the Adam optimization is used to predict the critical temperature data via holographic calculation with appropriate accuracy. …”
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Analysis and Implementation of the Crowbar Clamping Circuit for Surge Voltage Reduction in the DC Solid-State Circuit Breaker by Phanit Sok, Sung-Geun Song, Feel-Soon Kang

“…A significant challenge in DC SSCB is simulating the behavior with several types of MOV with the highly non-linear model of MOV. The equivalent non-linear model of the MOV used in this paper for simulation is determined through the curve fit function using the algorithm for optimization.…”
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Well logging super-resolution based on fractal interpolation enhanced by BiLSTM-AMPSO by Jian Han, Yu Deng, Bing Zheng, Zhimin Cao

“…Specifically, mutation factors are introduced into the particle swarm optimization (PSO) algorithm to enhance search accuracy. …”
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Impacts of inter-train distances on aerodynamic drag reduction in heavy-haul train groups by LYU Jun, XIANG Tao, SONG Zongying, GAO Guangjun

“…This paper analyzes the impacts of inter-train distances in this operational mode on the aerodynamic characteristics of trailing trains, using computational fluid dynamics (CFD) methods, based on the SST <italic>k</italic>-<italic>ω</italic> turbulence model. Initial algorithm validation was performed, and the results were compared with data from wind tunnel experiments conducted in a large low-speed wind tunnel at the China aerodynamics research and development center. …”
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A lightweight lattice-based group signcryption authentication scheme for Internet of things by XU Chuan, AI Xinghao, WANG Shanshan, ZHAO Guofeng, HAN Zhenzhen

“…In the key generation stage, the improved trapdoor diagonal matrix was designed to optimize the original image sampling algorithm required for key generation and reduce the overall time required for generating a large number of keys. …”
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Maximum Power Extraction in Photovoltaic Systems Using High-Performance Adaptive Control Approach by Ahmed Ouaret, Hocine Lehouche, Adel Oubelaid, Arvind Yadav, Boubekeur Mendil, Ievgen Zaitsev

“…These outcomes underscore the notable performance enhancements facilitated by the proposed algorithm. In conclusion, the developed control algorithm offers superior performance in optimizing power extraction and maintaining precise set point tracking for PV systems, leading to improved system efficiency and increased profitability.…”
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Machine Learning Applications in Gray, Blue, and Green Hydrogen Production: A Comprehensive Review by Xuejia Du, Shihui Gao, Gang Yang

“…Among these, green hydrogen—particularly via water electrolysis and biomass gasification—received the most attention, reflecting its central role in decarbonization strategies. ML algorithms such as artificial neural networks (ANNs), random forest (RF), and gradient boosting regression (GBR) have been widely applied to predict hydrogen yield, optimize operational conditions, reduce emissions, and improve process efficiency. …”
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KDFE: Robust KNN-Driven Fusion Estimator for LEO-SoOP Under Multi-Beam Phased-Array Dynamics by Jiaqi Yin, Ruidan Luo, Xiao Chen, Linhui Zhao, Hong Yuan, Guang Yang

“…This decision model overcomes the accuracy-robustness trade-off by matching algorithmic strengths to beam-specific dynamics, ensuring optimal performance during abrupt SNR transitions and high Doppler rates. …”
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Fingerprint Classification Based on Multilayer Extreme Learning Machines by Axel Quinteros, David Zabala-Blanco

“…While advanced classification algorithms, including support vector machines (SVMs), multilayer perceptrons (MLPs), and convolutional neural networks (CNNs), have demonstrated near-perfect accuracy (approaching 100%), their high training times limit their widespread applicability across institutions. …”
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GAT-Enhanced YOLOv8_L with Dilated Encoder for Multi-Scale Space Object Detection by Haifeng Zhang, Han Ai, Donglin Xue, Zeyu He, Haoran Zhu, Delian Liu, Jianzhong Cao, Chao Mei

“…According to the characteristics of space missions, an annotated dataset containing 8000 satellite and space station images is constructed, covering a variety of lighting, attitude and scale scenes, and providing benchmark support for model training and verification. Experimental results on the space object dataset reveal that the enhanced algorithm achieves a mean average precision (mAP) of 97.2%, representing a 2.1% improvement over the original YOLOv8_L. …”
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Abnormal Vibration Analysis of Low-floor Tram by Shuo LYU, Huanyun DAI, Qunsheng WANG

“…By establishing a vehicle dynamics model, the influence of the wheel on the different eccentricity is analyzed, and the vertical ride comfort is greatly improved by optimizing parameters of inter-vehicle longitudinal damper and secondary vertical damper. …”
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Distinguishing novel coronavirus influenza A virus pneumonia with CT radiomics and clinical features by Lianyu Sui, Huan Meng, Jianing Wang, Wei Yang, Lulu Yang, Xudan Chen, Liyong Zhuo, Lihong Xing, Yu Zhang, Jingjing Cui, Xiaoping Yin

“…After incorporating clinical features, the clinical model’s discriminatory and predictive efficacy further improved in testing sets (AUC, 0.669 vs. 0.820, P = 0.002). …”
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Drilling Condition Identification Method for Imbalanced Datasets by Yibing Yu, Huilin Yang, Fengjia Peng, Xi Wang

“…To address the challenges posed by class imbalance and temporal dependency in drilling condition data and enhance the accuracy of condition identification, this study proposes an integrated method combining feature engineering, data resampling, and deep learning model optimization. Firstly, a feature selection strategy based on weighted symmetrical uncertainty is employed, assigning higher weights to critical features that distinguish minority classes, thereby enhancing class contrast and improving the classification capability of the model. …”
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Empowering drones in vehicular network through fog computing and blockchain technology. by Shivani Wadhwa, Divya Gupta, Shalli Rani, Maha Driss, Wadii Boulila

“…The proposed algorithm dynamically plans drone trajectories and optimizes computation offloading. …”
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Research on the blockchain-based trusted ownership confirmation and value transfer system and its light weight of industrial data assets by WANG Dongchu, FU Yusun, YU Ya

“…The consensus protocol algorithm of the blockchain system was optimized based on the trustworthiness of nodes, reducing the probability of malicious attacks on nodes while improving the efficiency of system transaction consensus, achieving security and lightweight parallelism of the entire system. …”
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Intelligent deep learning for human activity recognition in individuals with disabilities using sensor based IoT and edge cloud continuum by Mohammed Maray

“…Initially, the IDLTHAR-PDST technique utilizes min-max normalization-based data pre-processing model to optimize sensor data consistency and enhance model performance. …”
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