研究论文

Cross-scenario impact damage prediction in concrete using peridynamics-trained Kolmogorov–Arnold networks with transfer learning

Xiaohu Yu, Junpeng Li, Jinlong Liu, Yan Li, Airong Chen, Yuzhuo Zhang, Haocheng Chang

The University of Melbourne　Southeast University　Tongji University　Shenyang Jianzhu University

来源International Journal of Impact Engineering

年份2026

DOI10.1016/j.ijimpeng.2026.105764

原文https://doi.org/10.1016/j.ijimpeng.2026.105764

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逐年被引趋势

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926

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30.45

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学术脉络

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工程

Numerical methods in engineering

Rock Mechanics and Modeling · Model Reduction and Neural Networks

参考文献 74

Dynamic fracture of concrete L-specimen: Experimental and numerical study

Joško Ožbolt, Natalija Bede, Akanshu Sharma · Engineering Fracture Mechanics · 2015

被引 80

An analytic expression for P/L for WA long rods into armor steel

C. E. Anderson, James D. Walker · AIP conference proceedings · 1996

被引 10

Transfer learning using computational intelligence: A survey

Jie Lü, Vahid Behbood, Hao Peng · Knowledge-Based Systems · 2015

被引 985

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引用本文 9

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Gaurav Jagad, Amit Thoriya · International Journal of Material Forming · 2026

被引 1

Deep Learning-Based Porosity Prediction of Concrete Under Freeze–Heaving Conditions Using Strain Fields

Yilong Guo, Yalin Li, Linhui Song · Mathematics · 2026

被引 0

Machine learning models with graphical user interfaces for overall gas holdup in slurry bubble column reactors

Manoj Kumar Beriya, Shantanu Roy · Next Chemical Engineering · 2026