Correction: Modeling and predicting the sensitivity of high-performance concrete compressive strength using machine learning methods

Yamani, Walaa Hussein Al; Ghunimat, Dalin Mohammad; Bisharah, Majdi

doi:10.1007/s42107-023-00658-6

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“…Modeling and sensitivity analysis of high-performance concrete to various factors were explored in another recent work. The emphasis was on the accurate forecasting of compressive strength for both traditional and high-performance concrete constructions, considering the intricate development processes [25].…”

Section: Literature Reviewmentioning

confidence: 99%

Comprehensive analysis of machine learning models for predicting concrete compressive strength

Saidjon Kamolov

2024

AMCS

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Predicting the compressive strength of concrete provides several benefits including insights into its durability, potential lifespan, and its suitability for specific construction projects. Recent advances in machine learning algorithms have prompted their application to compressive strength modeling and prediction. In this paper, we carry out a comprehensive comparative analysis of the existing machine learning algorithms. Unlike, other current studies in this domain, we consider the entire spectrum of algorithms ranging from basic linear models to advanced meta-learning methods. The results show that there exists a trade-off between speed and accuracy of the models. We find that while ensemble models such as stacking and gradient boost provide superior accuracy, they are significantly slower than linear models.

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Section: Literature Reviewmentioning

confidence: 99%

Comprehensive analysis of machine learning models for predicting concrete compressive strength

Saidjon Kamolov

2024

AMCS

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Fast prediction of the compressive strength of high-performance concrete through a k-nearest neighbor approach

Phan

2023

Asian J Civ Eng

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Correction: Modeling and predicting the sensitivity of high-performance concrete compressive strength using machine learning methods

Cited by 2 publications

References 0 publications

Comprehensive analysis of machine learning models for predicting concrete compressive strength

Comprehensive analysis of machine learning models for predicting concrete compressive strength

Fast prediction of the compressive strength of high-performance concrete through a k-nearest neighbor approach

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