Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
259519 | Construction and Building Materials | 2010 | 10 Pages |
Abstract
No-slump concrete (NSC) is defined as concrete having either very low or zero slump that traditionally used for prefabrication purposes. The sensitivity of NSC to its constituents, mixture proportion, compaction, etc., enforce some difficulties in the prediction of the compressive strength. In this paper, by considering concrete constituents as input variables, several regression, neural networks (NNT) and ANFIS models are constructed, trained and tested to predict the 28-days compressive strength of no-slump concrete (28-CSNSC). Comparing the results indicate that NNT and ANFIS models are more feasible in predicting the 28-CSNSC than the proposed traditional regression models.
Related Topics
Physical Sciences and Engineering
Engineering
Civil and Structural Engineering
Authors
Jafar Sobhani, Meysam Najimi, Ali Reza Pourkhorshidi, Tayebeh Parhizkar,