Turbulent Mechanisms for the Deep Convective Boundary Layer in the Taklimakan Desert by Lu Zhang, Hongsheng Zhang, Qianhui Li, Wei Wei, Xuhui Cai, Yu Song, Ali Mamtimin, Minzhong Wang, Fan Yang, Yu Wang, Chenglong Zhou

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Stability evaluation of tunnels in steeply dipping layered rock mass using numerical models: a case study by Eleyas Assefa, Kidusyared Tilahun, Siraj Mulugeta Assefa, Nagessa Zerihun Jilo, Lysandros Pantelidis, Costas Sachpazis

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Construction Method of CNC Machine Tool Digital Twin Model Based on the Four-Layer Framework by Fengye Pei, Suifan Chen, Qipeng Li, Shixiong Guo, Yuyuan Xi, Pengju Huang

“…Computer numerical control (CNC) machine tool as an important equipment of intelligent manufacturing, due to its complex structure and complicated working conditions, DT technology is troubled by model consistency in application. To construct the DT model more effectively and accurately, a four-layer modeling framework is proposed based on the working characteristics of CNC machine tools, including requirement layer, representation layer, interaction layer and implementation layer. …”
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Transport models for predicting spontaneous ignition of pressurized hydrogen released into a tube by Gang Luo, Wenping Zhang, Zixuan Yang, Lijing Zhang, Jinfeng Zhang

“…However, fundamental processes governing spontaneous ignition at the microscopic scale, such as transport models and ignition initiation, are not fully explained. …”
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Mathematical Modelling of Thin Layer Drying of Alfalfa (Medicago sativa L.) Varieties at Different Temperatures by Muhammed Taşova, Hakan Polatcı, Mahir Özkurt

“…In addition, the most suitable thin layer drying models were determined, which are important in controlling the drying processes and developing new product-specific dryers. …”
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Four-layer five-dimensional closed-loop model architecture for intelligent operational mission planning by WANG Wending, LIU Xiaohu, WANG Penglin, DONG Shuqin, ZHOU Shengnan

“…Then, based on the closed-loop process system, a four-layer five-dimensional closed-loop model architecture for intelligent operational mission planning is put forward. …”
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Accelerating automatic model finding with layer replications case study of MobileNetV2. by Kritpawit Soongswang, Chantana Chantrapornchai

“…Our experiments demonstrate the effectiveness of the automatic model finding process for layer replication, using both distributed data-parallel and concurrent training under different conditions. …”
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Comparison of Kolmogorov–Arnold Networks and Multi-Layer Perceptron for modelling and optimisation analysis of energy systems by Talha Ansar, Waqar Muhammad Ashraf

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Additional stress transfer model of double layer dielectric foundation on thin topsoil covered area by Chao GAO, Guocan TIAN, Naizhong XU, Yujun ZHANG

“…In view of the few and imperfect models for calculating the additional stress and the depth of load effect on thin topsoil layer area, it is necessary to further investigate the additional stress transfer model of double layer elastic medium foundation from the perspective of simple calculation process, fewer parameters and easy access. …”
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Distribution Network Security Situation Awareness Method Based on the Distribution Network Topology Layered Model by Yuhong Ouyang, Man Li, Wenqian Kang, Xiangbei Che, Ruixian Ye

“…In response to the rapid and accurate distribution network security situation awareness requirements, this paper proposes a distribution network security situation awareness method based the distribution network topology layered model. First, a hierarchical model of the distribution network topology under the premise of optimizing the location of the synchronous phasor measuring device is constructed. …”
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A two‐stage, four‐layer robust optimisation model for distributed cooperation in multi‐microgrids by Haobo Rong, Jianhui Wang, Honghai Kuang

“…The proposed model follows a two‐stage, four‐layer ‘min‐min‐max‐min’ structure. …”
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Exploring the Effects of Support Restoration on Pictorial Layers Through Multi-Resolution 3D Survey by Emma Vannini, Silvia Belardi, Irene Lunghi, Alice Dal Fovo, Raffaella Fontana

“…By processing and cross-comparing 3D point cloud data from both techniques, we quantified shape variations and evaluated their impact on the pictorial layers. …”
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Antenna Optimization Design Based on Deep Gaussian Process Model by Xin-Yu Zhang, Yu-Bo Tian, Xie Zheng

“…When using Gaussian process (GP) machine learning as a surrogate model combined with the global optimization method for rapid optimization design of electromagnetic problems, a large number of covariance calculations are required, resulting in a calculation volume which is cube of the number of samples and low efficiency. …”
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Comparison of classical, xgboost and neural network methods for parameter estimation in epidemic processes on random graphs by Ágnes Backhausz, Edit Bognár, Villő Csiszár, Damján Tárkányi, András Zempléni

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Applying the language acquisition model to the solution small language processing tasks by Dz. I. Kachkou

“…Based on the current understanding of the language acquisition and existing computer models of this process, the architecture of the system of small language processing, which is taught through modeling of ontogenesis, is proposed. …”
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A neural master equation framework for multiscale modeling of molecular processes: application to atomic-scale plasma processes by Shoubhanik Nath, Joseph R. Vella, David B. Graves, Ali Mesbah

“…The framework is demonstrated for multiscale modeling of Si atomic layer etching and reactive ion etching, where the learned NME-based surface kinetic models exhibit good predictive and extrapolative capabilities for predicting experimentally relevant observables as a function of process parameters. …”
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Modeling of quality characteristics of the surface layer hardened by free-moving indenters under rotating electromagnetic field by Valery A. Lebedev, Anatoly A. Kochubey, Irina V. Chumak

“…A comparative analysis of the experimental data obtained in the process of the magneto-dynamic processing with the calculated ones shows the applicability of the proposed models for predicting quality parameters of the hardened surface layer.…”
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Parametric evaluation and predictive modelling of formability in μ-SPIF process by Sahu Vijay Kumar, Das Purnendu, Adhikary Avishek, Bandyopadhyay Kaushik

“…Machine learning regression models e.g. Tri-layered Neural Network, Quadratic Support Vector Machine, and Gaussian Process Regression are developed based on experimental data to predict the formed height and the surface roughness. …”
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Establishment of a Prediction Model for the Residual Stress on the Surface Layer of Face Gears During Hot Rolling by Jin Yuanyuan, Xu Hongyu, Li Li, Zhang Fengshou, Wang Xiaoqiang, Zhang Guang

“…Taking the simulation results as data samples, the response surface method is used to establish the prediction model of residual compressive stress and compressive stress layer depth on the surface of hot rolling gear profiles, and the optimal process combination is obtained by taking the maximum peak value of residual compressive stress and the minimum depth of residual compressive stress layer as the optimization objective. …”
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High-Performance and Lightweight AI Model with Integrated Self-Attention Layers for Soybean Pod Number Estimation by Qian Huang

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