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Efficient neural network training method for unsteady flow field prediction based on data pool
Published 2025-12-01Get full text
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2106
A Comprehensive Analysis of Losses and Efficiency in a Buck ZCS Quasi-Resonant DC/DC Converter
Published 2025-06-01Get full text
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2107
Design and Analysis of an Ultra-Wideband High-Precision Active Phase Shifter in 0.18 μm SiGe BiCMOS Technology
Published 2025-05-01“…This paper presents an active phase shifter for phased array system applications, implemented using 0.18 μm SiGe BiCMOS technology. …”
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Thermal runaway and flame propagation in battery packs: numerical simulation and deep learning prediction
Published 2025-12-01“…The widespread application of lithium-ion battery technology faces a significant challenge from the inherent risk of thermal runaway and consequent fire spread. …”
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2110
A novel graph modeling method for GNN-based hypersonic aircraft flow field reconstruction
Published 2024-12-01Get full text
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2111
Determining the Strength of Structural Materials by Solving Inverse Problems of Thermoelasticity
Published 2025-04-01Get full text
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2112
Interpretable Deep Learning Model for Grape Leaf Disease Classification Based on EfficientNet with Grad-CAM Visualization
Published 2025-06-01“…Traditional manual inspection methods are inefficient and prone to human error, highlighting the need for an automated approach. …”
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2113
Efficient and generalizable nested Fourier-DeepONet for three-dimensional geological carbon sequestration
Published 2024-12-01Get full text
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Blast loading prediction in a typical urban environment based on Bayesian deep learning
Published 2025-12-01Get full text
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Modelling flame-to-fuel heat transfer by deep learning and fire images
Published 2024-12-01“…Results show that the proposed AI algorithm trained by flame images can predict both the convective and radiative heat flux distributions on the condensed fuel surface with a relative error below 20%, based on the input of real-time flame morphology that can be captured by a larger grid size. …”
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Monitoring water quality parameters using multi-source data-driven machine learning models
Published 2025-12-01“…Therefore, the findings confirmed the importance of environmental variables in water quality inversion and provided a theoretical basis for the optimization and application of future water quality monitoring systems.…”
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Machine Learning Using Approximate Computing
Published 2025-04-01“…Approximate computation has emerged as a promising alternative to accurate computation, particularly for applications that can tolerate some degree of error without significant degradation of the output quality. …”
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