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https://hdl.handle.net/2440/129978
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Type: | Journal article |
Title: | Evaluation of mechanical properties of concretes containing coarse recycled concrete aggregates using multivariate adaptive regression splines (MARS), M5 model tree (M5Tree), and least squares support vector regression (LSSVR) models |
Author: | Gholampour, A. Mansouri, I. Kisi, O. Ozbakkaloglu, T. |
Citation: | Neural Computing and Applications, 2020; 32(1):295-308 |
Publisher: | Springer (part of Springer Nature) |
Issue Date: | 2020 |
ISSN: | 0941-0643 1433-3058 |
Statement of Responsibility: | Aliakbar Gholampour, Iman Mansouri, Ozgur Kisi, Togay Ozbakkaloglu |
Abstract: | This paper investigates the application of three artificial intelligence methods, including multivariate adaptive regression splines (MARS), M5 model tree (M5Tree), and least squares support vector regression (LSSVR) for the prediction of the mechanical behavior of recycled aggregate concrete (RAC). A large and reliable experimental test database containing the results of 650 compressive strength, 421 elastic modulus, 152 flexural strength, and 346 splitting tensile strength tests of RACs with no pozzolanic admixtures assembled from the published literature was used to train, test, and validate the three data-driven-based models.The results of themodel assessment showthat theLSSVRmodel provides improved accuracy over the existingmodels in the prediction of the compressive strength of RACs. The results also indicate that, although all three models provide higher accuracy than the existing models in the prediction of the splitting tensile strength of RACs, only the performance of the LSSVR model exceeds those of the best-performing existing models for the flexural strength of RACs. The results of this study indicate that MARS, M5Tree, and LSSVR models can provide close predictions of the mechanical properties of RACs by accurately capturing the influences of the key parameters. This points to the possibility of the application of these three models in the predesign and modeling of structures manufactured with RACs. |
Keywords: | Recycled aggregate concrete (RAC); Mechanical properties; Least squares support vector regression (LSSVR); M5 model tree (M5Tree); Multivariate adaptive regression splines (MARS) |
Description: | Published online: 1 August 2018 |
Rights: | © The Natural Computing Applications Forum 2018 |
DOI: | 10.1007/s00521-018-3630-y |
Published version: | http://dx.doi.org/10.1007/s00521-018-3630-y |
Appears in Collections: | Aurora harvest 8 Civil and Environmental Engineering publications |
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