Agile DQN: adaptive deep recurrent attention reinforcement learning for autonomous UAV obstacle avoidance by Fadi AlMahamid, Katarina Grolinger

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Trade-Space Exploration With Data Preprocessing and Machine Learning for Satellite Anomalies Reliability Classification by Abdul Mutholib, Nadirah Abdul Rahim, Teddy Surya Gunawan, Mira Kartiwi

“…Leveraging a Seradata dataset spanning 66 years and 4,455 satellite records, the framework systematically evaluates four data cleaning methods, four data transformation techniques, five normalization strategies, and seven machine learning algorithms across 480 configurations. The optimal configuration, comprising Iterative Imputation, FastText, Robust Scaling, and Decision Tree, achieved the highest testing accuracy of 95.74% with competitive computational efficiency. …”
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Coupling HEC-RAS and AI for River Morphodynamics Assessment Under Changing Flow Regimes: Enhancing Disaster Preparedness for the Ottawa River by Mohammad Uzair Anwar Qureshi, Afshin Amiri, Isa Ebtehaj, Silvio José Guimere, Juraj Cunderlik, Hossein Bonakdari

“…Despite significant advancements in flood forecasting using machine learning (ML) algorithms, recent events have revealed hydrological behaviors deviating from historical model development trends. …”
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Multi-exit Kolmogorov–Arnold networks: enhancing accuracy and parsimony by James Bagrow, Josh Bongard

“…This architecture provides deep supervision that improves training while discovering the right level of model complexity for each task. …”
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AI-Enhanced Design and Application of High School Geography Field Studies in China: A Case Study of the Yellow (Bohai) Sea Migratory Bird Habitat Curriculum by Binglin Liu, Weijia Zeng, Weijiang Liu, Yi Peng, Nini Yao

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THEORETICAL AND METHODOLOGICAL ASPECTS OF USING INFORMATION ANDCOGNITIVE TECHNOLOGIES IN THE TRAINING OF TRANSPORT SPECIALISTS by Lavrentieva Olena, Krupskyi Oleksandr

“…It has been established that information-cognitive technologies combine methods and algorithms based on insights into the cognition processes, learning, communication, and information processing, grounded in the achievements of neuroscience, digital and information technologies, and the mathematical modelling of consciousness. …”
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Lung Cancer Prediction Using an Enhanced Neutrosophic Set Combined with a Machine Learning Approach by Vakeel A. Khan, Asheesh Kumar Yadav, Mohammad Arshad, Nadeem Akhtar

“…To address this issue, we propose an Enhanced Neutrosophic Set (ENS) framework integrated with machine learning algorithms to improve the prediction accuracy of lung cancer. …”
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Quantum Computing and Machine Learning in Medical Decision-Making: A Comprehensive Review by James C. L. Chow

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Modelica-Based Energy Management of PEMFC Hybrid Power System of Vehicle by Keshu Zhang, Jiandong Jia, Xiaodan Shangguan, Jing Dong

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Implementation of an Intelligent Controller Based on Neural Networks for the Simulation of Pressure Swing Adsorption Systems by Moises Ramos-Martinez, Jorge A. Brizuela-Mendoza, Carlos A. Torres-Cantero, Gerardo Ortiz-Torres, Felipe D. J. Sorcia-Vázquez, Mario A. Juarez, Jair de Jesús Cambrón Navarrete, Juan Carlos Mixteco-Sánchez, Mayra G. Mena-Enriquez, Rafael Murrieta Yescas, Jesse Y. Rumbo-Morales

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Dynamic Path Planning for Vehicles Based on Causal State-Masking Deep Reinforcement Learning by Xia Hua, Tengteng Zhang, Jun Cao

“…Extensive experimental results demonstrate that this method significantly enhances the convergence of the TD3 algorithm and effectively improves its performance in dynamic path planning.…”
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Encoding-Based Machine Learning Approach for Health Status Classification and Remote Monitoring of Cardiac Patients by Sohaib R. Awad, Faris S. Alghareb

“…In short, this study aims to explore how ML algorithms can enhance diagnostic accuracy, improve real-time monitoring, and optimize treatment outcomes. …”
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Feature Transformation-Based Few-Shot Class-Incremental Learning by Xubo Zhang, Yang Luo

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Effective Detection of Malicious Uniform Resource Locator (URLs) Using Deep-Learning Techniques by Yirga Yayeh Munaye, Aneas Bekele Workneh, Yenework Belayneh Chekol, Atinkut Molla Mekonen

“…Through iterative refinement, we optimized the model’s performance to maximize its effectiveness. …”
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Single-Stage Entity–Relation Joint Extraction of Pesticide Registration Information Based on HT-BES Multi-Dimensional Labeling Strategy by Chenyang Dong, Shiyu Xi, Yinchao Che, Shufeng Xiong, Xinming Ma, Lei Xi, Shuping Xiong

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A VIKOR-Based Sequential Three-Way Classification Ranking Method by Wentao Xu, Jin Qian, Yueyang Wu, Shaowei Yan, Yongting Ni, Guangjin Yang

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A Lightweight and Efficient Plant Disease Detection Method Integrating Knowledge Distillation and Dual-Scale Weighted Convolutions by Xiong Yang, Hao Wang, Qi Zhou, Lei Lu, Lijuan Zhang, Changming Sun, Guilu Wu

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A Semi-Supervised-Learning-Aided Explainable Belief Rule-Based Approach to Predict the Energy Consumption of Buildings by Sami Kabir, Mohammad Shahadat Hossain, Karl Andersson

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Hybrid Multi-Granularity Approach for Few-Shot Image Retrieval with Weak Features by Aiguo Lu, Zican Li, Yanwei Liu, Pandi Liu, Ke Wang

“…The optimized loss function further enhances the robustness and distinctiveness of features, improving retrieval accuracy. …”
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Data Augmentation for Voiceprint Recognition Using Generative Adversarial Networks by Yao-San Lin, Hung-Yu Chen, Mei-Ling Huang, Tsung-Yu Hsieh

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