Data Cleansing & Overfitting Check for Interpretable ML in Concrete Design – a punching shear paradigm

نویسندگان

چکیده

Abstract Evaluation of shear capacity is crucial for existing concrete buildings and bridges. Shear failure can cause an abrupt brittle loss load‐carrying capacity, leading to load redistribution progressive collapse. An internationally research scietific discourse actively ongoing on the best prediction model shear, torsion, punching with no clear consensus. A machine learning‐based strength suggested accurate using Gaussian Process Regression Support Vector models. Data elaboration thorough evaluation are needed enhance model's performance interpretability. The paper discusses critical methodological steps based authors' experience developing ML‐models structural design against 544 full‐scale tests.

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ژورنال

عنوان ژورنال: ce/papers

سال: 2023

ISSN: ['2509-7075']

DOI: https://doi.org/10.1002/cepa.2057