Accurately predicting the mechanical behavior of deteriorated reinforced concrete components using natural intelligence-integrated Machine learners

Nguyen, Thanh-Hung; Tran, Duc-Hoc; Nguyen, Ngoc-Mai; Vuong, Hoang-Thach; Chien-Cheng, Chen; Cao, Minh-Tu

doi:10.1016/j.conbuildmat.2023.133753

Construction and Building Materials

2023

DOI: 10.1016/j.conbuildmat.2023.133753

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Accurately predicting the mechanical behavior of deteriorated reinforced concrete components using natural intelligence-integrated Machine learners

Thanh-Hung Nguyen,

Duc-Hoc Tran,

Ngoc-Mai Nguyen

et al.

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Cited by 4 publications

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Estimating Deformation of Geogrid-Reinforced Soil Structures Using Hybrid LSSVR Analysis

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Shing-Wen,

Hsiao

2024

Int. J. of Geosynth. and Ground Eng.

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Parametric study on global estimation models for compressive strength adopting various machine learning algorithms in concrete

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2024

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Accurately predicting the mechanical behavior of deteriorated reinforced concrete components using natural intelligence-integrated Machine learners

Cited by 4 publications

References 61 publications

Estimating Deformation of Geogrid-Reinforced Soil Structures Using Hybrid LSSVR Analysis

Estimating Deformation of Geogrid-Reinforced Soil Structures Using Hybrid LSSVR Analysis

Parametric study on global estimation models for compressive strength adopting various machine learning algorithms in concrete

A study on improving energy flexibility in building engineering through generalized prediction models: Enhancing local bearing capacity of concrete for engineering structures

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