Journal ArticleDOI
Predicting concrete compressive strength using hybrid ensembling of surrogate machine learning models
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TLDR
The newly constructed HENSM model is very potential to be a new alternative in handling the overfitting issues of CML models and hence, can be used to predict the concrete CS, including the design of less polluting and more sustainable concrete constructions.About:
This article is published in Cement and Concrete Research.The article was published on 2021-07-01. It has received 166 citations till now. The article focuses on the topics: Overfitting & Multivariate adaptive regression splines.read more
Citations
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Journal ArticleDOI
Machine learning for structural engineering: A state-of-the-art review
TL;DR: An overview of ML techniques for structural engineering is presented in this article with a particular focus on basic ML concepts, ML libraries, open-source Python codes, and structural engineering datasets.
Journal ArticleDOI
Interpretable Ensemble-Machine-Learning models for predicting creep behavior of concrete
TL;DR: Wang et al. as mentioned in this paper used three ensemble machine learning (EML) models: Random Forest (RF), Extreme Gradient Boosting Machine (XGBoost) and Light Gradient boosting machine (LGBM) to predict concrete creep behavior.
Journal ArticleDOI
Interpretable Ensemble-Machine-Learning models for predicting creep behavior of concrete
TL;DR: Wang et al. as mentioned in this paper used three ensemble machine learning (EML) models: Random Forest (RF), Extreme Gradient Boosting Machine (XGBoost) and Light Gradient boosting machine (LGBM) to predict concrete creep behavior.
Journal ArticleDOI
ELM-based adaptive neuro swarm intelligence techniques for predicting the California bearing ratio of soils in soaked conditions
TL;DR: It can be concluded that the newly constructed ELM-based ANSI models can solve the difficulties in tuning the acceleration coefficients of SPSO by the trial-and-error method for predicting the CBR of soils and be further applied to other real-time problems of geotechnical engineering.
Journal ArticleDOI
Bonding behavior of concrete matrix and alkali-activated mortar incorporating nano-SiO2 and polyvinyl alcohol fiber: Theoretical analysis and prediction model
TL;DR: In this paper, the effects of polyvinyl alcohol (PVA) fiber and nano-SiO2 (NS) contents on the bonding behavior of two-interfaced shear samples were explored.
References
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Journal ArticleDOI
Ensemble Support Vector Machine Algorithm for Reliability Estimation of a Mining Machine
TL;DR: Study results demonstrate that the developed model performs well with high accuracy in the prediction of dumper failure, and a comparison with other methods demonstrates the superiority of the proposed ensemble SVM model.
Journal ArticleDOI
Multivariate adaptive regression spline (MARS) and least squares support vector machine (LSSVM) for OCR prediction
Pijush Samui,Pradeep Kurup +1 more
TL;DR: This article investigates the feasibility of multivariate adaptive regression spline and least squares support vector machine (LSSVM) for the prediction of over consolidation ratio (OCR) of clay deposits based on Piezocone Penetration Tests (PCPT) data.
Journal ArticleDOI
Fuzzy inference system to formulate compressive strength and ultimate strain of square concrete columns wrapped with fiber-reinforced polymer
TL;DR: The outputs of the proposed FIS models agree favorably with the test data and outperform the existing models by providing more accurate prediction of both strength and strain capacity.
Book ChapterDOI
Intelligent Modeling and Prediction of Elastic Modulus of Concrete Strength via Gene Expression Programming
TL;DR: The results show that GEP can be an effective method for deriving simplified and precise formulations for the elastic modulus of NSC and HSC and indicates that the GEP predictions are more accurate than other methods.
Journal ArticleDOI
Modeling Portland Blast-Furnace Slag Cement High-Performance Concrete
Carlos Videla,Cristian Gaedicke +1 more
TL;DR: In this article, the authors focused on portland blast-furnace slag cement high performance concrete (HPC), with specified 28-day compressive strengths of 60-110 MPa.