Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Estimating Compressive Strength of High Performance Concrete with Gaussian Process Regression Model
This research carries out a comparative study to investigate a machine learning solution that employs the Gaussian Process Regression (GPR) for modeling compressive strength of high-performance concrete (HPC). This machine learning approach is utilized to establish the nonlinear functional mapping between the compressive strength and HPC ingredients. To train and verify the aforementioned prediction model, a data set containing 239 HPC experimental tests, recorded from an overpass construction project in Danang City (Vietnam), has been collected for this study. Based on experimental outcomes, prediction results of the GPR model are superior to those of the Least Squares Support Vector Machine and the Artificial Neural Network. Furthermore, GPR model is strongly recommended for estimating HPC strength because this method demonstrates good learning performance and can inherently express prediction outputs coupled with prediction intervals.
Estimating Compressive Strength of High Performance Concrete with Gaussian Process Regression Model
This research carries out a comparative study to investigate a machine learning solution that employs the Gaussian Process Regression (GPR) for modeling compressive strength of high-performance concrete (HPC). This machine learning approach is utilized to establish the nonlinear functional mapping between the compressive strength and HPC ingredients. To train and verify the aforementioned prediction model, a data set containing 239 HPC experimental tests, recorded from an overpass construction project in Danang City (Vietnam), has been collected for this study. Based on experimental outcomes, prediction results of the GPR model are superior to those of the Least Squares Support Vector Machine and the Artificial Neural Network. Furthermore, GPR model is strongly recommended for estimating HPC strength because this method demonstrates good learning performance and can inherently express prediction outputs coupled with prediction intervals.
Estimating Compressive Strength of High Performance Concrete with Gaussian Process Regression Model
Nhat-Duc Hoang (Autor:in) / Anh-Duc Pham (Autor:in) / Quoc-Lam Nguyen (Autor:in) / Quang-Nhat Pham (Autor:in)
2016
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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METHOD FOR ESTIMATING COMPRESSIVE STRENGTH OF CONCRETE
| Europäisches Patentamt | 2015
Prediction of compressive strength of concrete using multiple regression model
| British Library Online Contents | 2013
Compressive Strength Prediction of High-Strength Concrete Using Regression and ANN Models
| Springer Verlag | 2018