Hybrid Reinforcement Learning-Based Collision Avoidance Algorithm for Autonomous Vehicle Clusters by Chubing Guo, Jianshe Wu, Panzheng Luo, Zhigang Wang, Kai Zhang, Ziyi Yang, Zengfa Dou, Kan Song

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Design and Construction of Multimedia Smart English Teaching Platform Based on RBF Algorithm by Qianbo Li

“…The practice has proved that the method proposed in this paper is effective and has certain research value and positive significance for the research on English teaching.…”
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An improved YOLOv5n algorithm for detecting surface defects in industrial components by Jia-Hui Tian, Xue-Feng Feng, Feng Li, Qing-Long Xian, Zhen-Hong Jia, Jie-Liang Liu

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Problems of Algorithms Development to Determine Quality of Topic Models Ensembles for Make Rubricators by A. P. Shiryaev, A. R. Fedorov, P. A. Fedorov, L. G. Gagarina, E. M. Portnov

“…The concept for quality evaluation of thematic models ensemble, which uses the simple voting algorithm, was explored and proposed for further researches.…”
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Cancellation of cloud shadow effects in the absorbing aerosol index retrieval algorithm of TROPOMI by V. J. H. Trees, V. J. H. Trees, P. Wang, P. Stammes, L. G. Tilstra, D. P. Donovan, D. P. Donovan, A. P. Siebesma

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Estimating latent heat flux of subtropical forests using machine learning algorithms by Harekrushna Sahu, Pramit Kumar Deb Burman, Palingamoorthy Gnanamoorthy, Qinghai Song, Yiping Zhang, Huimin Wang, Yaoliang Chen, Shusen Wang

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Evaluating the Efficiency of Nature-Inspired Algorithms for Finite Element Optimization in the ANSYS Environment by Antonino Cirello, Tommaso Ingrassia, Antonio Mancuso, Giuseppe Marannano, Agostino Igor Mirulla, Vito Ricotta

“…The performance of each optimizer was assessed in three case studies. The first two are spatial truss structures, one comprising 22 bars and the other 25 bars, commonly used in structural optimization research. …”
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Prognostic algorithm for early diagnosis of subcritical conditions as predictors of sudden cardiac death by A. V. Bykov, P. S. Azarova, S. A. Parkhomenko, A. V. Bykov, A. V. Polyakova, M. V. Alymova, A. V. Vinnikov

“…In parallel with standard protocols for the management of severe somatic patients (chronic obstructive pulmonary disease, chronic kidney disease, hepatocellular failure), based on the proposed algorithm with an integral assessment of critical conditions, using the MCA decision rule in the main group in 30,5% of cases, subcritical stage was revealed, followed by targeted treatment and preventive support. …”
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Prediction of Electrical Grid Stability Using Naïve Bayes and K-Means Algorithm by Baik Budi, Muhammad Ilhamdi Rusydi, Reivan Arya Witama, Queen Hesti Ramadhamy, Refki Budiman

“…Data set for this research is public dataset from Kaggle. The main goal of the research is to develop an accurate and efficient predictive model. …”
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Quantitative and Spatially Explicit Clustering of Urban Grocery Shoppers in Montreal: Integrating Loyalty Data with Synthetic Population by Duo Zhang, Laurette Dubé, Antonia Gieschen, Catherine Paquet, Raja Sengupta

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3-Dimensional Spatial Analysis of Parking Lot Wall Scratch Using Mobile Point Cloud Data by Y. Li, C. Ye, Y. Zhang, Z. Kang

“…A novel approach integrating YOLOv10 object detection and PTv3 point cloud processing algorithms is developed to detect and localize scratches, while spatial analysis evaluates design factors affecting scratch distribution. …”
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Migration and commuting interactions fields: a new geography with community detection algorithm? by Isabelle Thomas, Arnaud Adam, Ann Verhetsel

“…They give the opportunity to remind that researchers have to control the impact of their methodological choices and that each type of data leads to a different geographical partitioning, with one major unexpected common spatial feature in Belgium: the pre-eminence of the provincial borders. …”
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Evaluating visitor perception and spatial preferences of various museums based on machine learning from 2016 to 2024. by Yuandi Jiang, Kalyna Pashkevych, Shibo Bi

“…Based on the comprehensive perspective of typology and spatio-temporal dynamic evolution, this study not only provides empirical support for museum space optimization, but also provides new ideas and strategies for functional research and methodological insights of public spaces.…”
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Comprehensive Analysis of Lightweight Cryptographic Algorithms for Battery-Limited Internet of Things Devices by Nahom Gebeyehu Zinabu, Yihenew Wondie Marye, Kula Kekeba Tune, Samuel Asferaw Demilew

“…The study’s conclusion emphasizes how urgently more research is needed to create cryptographic solutions that can sufficiently safeguard IoT devices.…”
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A Systematic Review of Mind Maps, STEM Education, Algorithmic and Procedural Learning by Chrysovalantis Kefalis, Constantine Skordoulis, Athanasios Drigas

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Prediction and Optimization of Civil Aviation Flight Delays Based on Machine Learning Algorithms by Qingwei Zhong, Yingxue Yu, Yiru Huang, Tianhang Zhang

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Parallel CUDA-Based Optimization of the Intersection Calculation Process in the Greiner–Hormann Algorithm by Jiwei Zuo, Junfu Fan, Kuan Li, Qingyun Liu, Yuke Zhou, Yi Zhang

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A Fallback Localization Algorithm for Automated Vehicles Based on Object Detection and Tracking by Mario Rodriguez-Arozamena, Jose Matute, Javier Araluce, Lukas Kuschnig, Christoph Pilz, Markus Schratter, Joshue Perez Rastelli, Asier Zubizarreta

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Parameter Identification in Triple-Diode Photovoltaic Modules Using Hybrid Optimization Algorithms by Dhiaa Halboot Muhsen, Haider Tarish Haider, Yaarob Al-Nidawi

“…Identifying the parameters of a triple-diode electrical circuit structure in PV modules is a critical issue, and it has been regarded as an important research area. Accordingly, in this study, a differential evolution algorithm (DEA) is hybridized with an electromagnetism-like algorithm (EMA) in the mutation stage to enhance the reliability and efficiency of the DEA. …”
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Neighborhood conditional mutual information entropy attribute reduction algorithm for hybrid data by Haibo LAN

“…Attribute reduction is an important research content of the rough set theory.Its main purpose is to eliminate irrelevant attributes in information systems, reduce data dimensions and improve data knowledge discovery performance.However, most of the attribute reduction methods based on a rough set do not consider the dependence between attributes, which makes the final attribute reduction result have some redundant attributes.An attribute reduction algorithm based on neighborhood conditional mutual information entropy was proposed.Firstly, based on the traditional neighborhood entropy, a hybrid neighborhood mutual information entropy model and a hybrid neighborhood conditional mutual information entropy model were proposed for hybrid data.Then, the two entropy models were used to evaluate the attribute dependence and attribute heuristic search of the hybrid information system, and an attribute reduction algorithm was designed.Finally, through the experimental analysis of UCI data sets, it was proved that the algorithm had higher attribute reduction performance.…”
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