Alpine Meadow Fractional Vegetation Cover Estimation Using UAV-Aided Sentinel-2 Imagery by Kai Du, Yi Shao, Naixin Yao, Hongyan Yu, Shaozhong Ma, Xufeng Mao, Litao Wang, Jianjun Wang

“…The results showed that: (1) Machine learning algorithms based on Sentinel-2 and UAV imagery effectively improved the accuracy of FVC estimation in alpine meadows. …”
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Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data by W. Bang, J. T. Carlin, K. Kim, A. V. Ryzhkov, A. V. Ryzhkov, G. Liu, G. Lee

“…We thus explore the effects of the SBM's microphysics scheme on the extent of melting in cases of misdiagnosed RA. An optimized SBM that uses the climatological snow density–diameter relationship for the Pyeongchang region produces an increased amount of melting and achieves improved skill scores compared to the current SBM, which uses a snow density–diameter relationship for the Colorado region.…”
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Research status of gearboxes for high-power nuclear power circulation pumps by WEI Fude, WANG Huanhuan, YANG Shuncheng

“…Many scholars are committed to in-depth research on high-power nuclear power circulating pump gearboxes from the perspectives of dynamics, mechanical design, big data, optimization algorithms, etc., in response to the above-mentioned issues. …”
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A Precise Oxide Film Thickness Measurement Method Based on Swept Frequency and Transmission Cable Impedance Correction by Yifan Li, Qi Xiao, Lisha Peng, Songling Huang, Chaofeng Ye

“…A swept frequency signal-processing algorithm is developed to separate the parameters and calculate oxide film thickness. …”
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A Matching Game for LLM Layer Deployment in Heterogeneous Edge Networks by Benedetta Picano, Dinh Thai Hoang, Diep N. Nguyen

“…Executing the inference of foundation models in a distributed manner presents significant challenges, particularly in optimizing both computing and communication resources. …”
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Deep neural network approach integrated with reinforcement learning for forecasting exchange rates using time series data and influential factors by T. Soni Madhulatha, Dr. Md. Atheeq Sultan Ghori

“…The algorithm leverages the strengths of both deep learning and reinforcement learning to achieve improved predictive accuracy and adaptability. …”
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Edge-Fog Computing-Based Blockchain for Networked Microgrid Frequency Support by Ying-Yi Hong, Francisco I. Alano, Yih-der Lee, Chia-Yu Han

“…The proposed approach integrates an edge–fog hierarchical blockchain architecture with a Long Short-Term Memory Model-Free Predictive Controller (LSTM-MFPC). The parameters and hyperparameters of the LSTM-MFPC are optimized using the Bayesian Adaptive Direct Search (BADS) algorithm. …”
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Causation Analysis of Marine Traffic Accidents Using Deep Learning Approaches: A Case Study from China’s Coasts by Zelin Zhao, Xingyu Liu, Lin Feng, Manel Grifoll, Hongxiang Feng

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Machine learning combined with multi-omics to identify immune-related LncRNA signature as biomarkers for predicting breast cancer prognosis by Yuxing Liu, Jintao Chen, Daifeng Yang, Chenming Liu, Chunhui Tang, Shanshan Cai, Yingxuan Huang

“…Utilizing transcriptomic and gene expression data from TCGA and GEO databases, 72 immune-related lncRNAs were identified through weighted gene co-expression network analysis (WGCNA) and ImmuLncRNA algorithms. The model was further optimized using 101 combinations of 10 machine learning approaches, ultimately constructing an immune-related lncRNA signature(IRLS) scoring system comprising nine key lncRNAs. …”
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Understanding visitor flow and behaviour in developing tourism-service-oriented villages by space syntax methodologies: a case study of Tabian Rural Section of Qingshan Village, Ha... by Shuqin Wang, Yan Huang, Tianjie Li

“…This study innovatively combines space syntax models for extended application in the research of rural BEs, providing guidance for optimizing strategies to improve spatial configuration in homogeneous villages.…”
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ECMS-Based MPC Strategy for Multi-Mode Hybrid Electric Trucks by Longjian Li, Changqing Du, Xiangyu Gongye, Jinhai Wang

“…To address the adaptive energy management optimization challenge of a hybrid powertrain system consisting of an internal combustion engine and dual electric motors, an Equivalent Consumption Minimization Strategy (ECMS) is introduced into the Model Predictive Control (MPC) framework. …”
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Remote Sensing Image Detection Method Combining Dynamic Convolution and Attention Mechanism by Yunfei Zhang, Ming Chen, Cong Chen

“…The improved model achieved an mAP of 83.0%, with accuracy improvements of 85.0%, 2.0%, and 5.0% compared to the baseline. …”
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Kinematic analysis, methods and experimental studies of robot navigator movements on mecanum wheels by Sladkova L.A., Pshibiev A.M.

“…In order to verify and evaluate the effectiveness of the localization and path planning algorithm in order to improve the control system of the mobile platform on mecanum wheels, modeling and simulation of the presented model were carried out, which made it possible to assess the kinematic parameters of the platform to achieve better results. …”

Frequency stabilization of a sophisticated multi-area interconnected hybrid power system considering non-inertia sources by Diaa M. Gawad, Gaber Magdy, M.A. Ebrahim, Eduard Petlenkov

“…This study accounts for various loading scenarios and system nonlinearities to validate the algorithm’s effectiveness. Furthermore, the superior performance of the RUN optimizer is verified by contrasting its results with other widely recognized optimization techniques, such as the Ant Lion optimizer (ALO) and Chernobyl disaster optimizer (CDO). …”
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Real-time temperature prediction of large-scale lithium battery module driven by data based on few measurement points by Jiajie HAN, Qingyang YUAN, Yu LI, Bo ZHANG, Ke XUE, Tian LAN

“…Integrating Gappy POD with other models can improve the overall efficiency, safety, and reliability of energy storage systems, driving advancements in smart and sustainable energy management solutions.…”
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Machine learning as a tool for diagnostic and prognostic research in coronary artery disease by B. I. Geltser, M. M. Tsivanyuk, K. I. Shakhgeldyan, V. Yu. Rublev

“…It is assumed that the improvement of ML-based models and their introduction into clinical practice will help support medical decision-making, increase the effectiveness of treatment and optimize health care costs.…”
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STATE PREDICTION OF WIND TURBINE GENERATOR BASED ON K-CNN AND N-GRU (MT) by CHAI Tong, YUAN YiPing, MA JunYan, FAN PanPan

“…Then, to solve the problem of parameter optimization of the traditional GRU algorithm, the neural network architecture search was used to improve the GRU algorithm, and the N-GRU model was obtained. …”
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Dissertation council in the state scientific certification system: Organizational and management mechanisms of digital transformation by Sergey I. Pakhomov, Elena A. Loginova, Oleg V. Kulyamin, Mikhail P. Petrov

“…The integration of the electronic document management system using the platform Gosuslugi has shortened the list of required documents and reduced the timeframes for providing the service. We propose an algorithm for the transition to a registry-based model that increases the transparency and accessibility of information about dissertation councils, and identify the promising forms of council organization, including one-time councils, considering best practices of degree-awarding bodies. …”
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Prediction of Shield Tunneling Attitude Based on WM-CTA Method by GAO Su, CHEN Cheng

“…To ensure that shield tunneling closely aligns with the designed alignment and to improve engineering construction quality, this study proposes a novel shield attitude prediction model, called WM-CTA, based on deep learning technology. …”
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Dynamic Error Compensation Control of Direct-Driven Servo Electric Cylinder Terminal Positioning System by Mingwei Zhao, Lijun Liu, Zhi Chen, Qinghua Yang, Xiaowei Tu

“…Then, a model to observe the dynamic error of the DDSEC-TPS was established using the improved beetle antennae search algorithm backpropagation neural network (IBAS-BPNN) prediction model according to the rigid–flexible deformation error theory of feed motion, and the observed dynamic error was compensated for in the vector control strategy of the DDSEC-TPS. …”
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