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Prediction of Compressive Strength of Rubberized Concrete Using Ordinary Least Squares Regression Model
Rubberized concrete (popularly known as Rubcrete) is a type of concrete in which crumb rubber replaces some amount of fine sand particles as fine aggregates. In this paper, ordinary least squares (OLS) regression was deployed to check its reliability in terms of predicting the compressive strength of rubcrete. To prepare the training data set for the model, concrete samples were prepared with percentage of rubber as a component of fine aggregate varying from 0 to 40% in increments of 5 percentage points. Each sample mix was tested for its compressive strength after intervals of 7, 14 and 28 days, respectively. Upon training the model with relevant input parameters, it predicted the compressive strength of rubcrete with a fair degree of accuracy. The score and mean squared error (MSE) were evaluated for the OLS model to find its general performance. For the model, a score of 0.959 and mean squared error of 1.745 indicated that the model was efficient and reliable.
Prediction of Compressive Strength of Rubberized Concrete Using Ordinary Least Squares Regression Model
Rubberized concrete (popularly known as Rubcrete) is a type of concrete in which crumb rubber replaces some amount of fine sand particles as fine aggregates. In this paper, ordinary least squares (OLS) regression was deployed to check its reliability in terms of predicting the compressive strength of rubcrete. To prepare the training data set for the model, concrete samples were prepared with percentage of rubber as a component of fine aggregate varying from 0 to 40% in increments of 5 percentage points. Each sample mix was tested for its compressive strength after intervals of 7, 14 and 28 days, respectively. Upon training the model with relevant input parameters, it predicted the compressive strength of rubcrete with a fair degree of accuracy. The score and mean squared error (MSE) were evaluated for the OLS model to find its general performance. For the model, a score of 0.959 and mean squared error of 1.745 indicated that the model was efficient and reliable.
Prediction of Compressive Strength of Rubberized Concrete Using Ordinary Least Squares Regression Model
Lecture Notes in Civil Engineering
Gupta, Ashok Kumar (editor) / Shukla, Sanjay Kumar (editor) / Azamathulla, Hazi (editor) / Kala, Prabhat (author) / Upadhya, Shivam (author) / Asthana, Pradhyumna (author) / Goyal, Pradeep K. (author)
Advances in Construction Materials and Sustainable Environment ; Chapter: 26 ; 331-339
2021-12-15
9 pages
Article/Chapter (Book)
Electronic Resource
English
Prediction of density and compressive strength for rubberized concrete blocks
British Library Online Contents | 2011
Prediction of density and compressive strength for rubberized concrete blocks
| Online Contents | 2011