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Advances in Materials Research Volume 11, Number 1, March 2022 , pages 75-90 DOI: https://doi.org/10.12989/amr.2022.11.1.075 |
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Comparison of machine learning algorithms to evaluate strength of concrete with marble powder |
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Nitisha Sharma, Ankita Upadhya, Mohindra S. Thakur and Parveen Sihag
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| Abstract | ||
| In this paper, functionality of soft computing algorithms such as Group method of data handling (GMDH), Random forest (RF), Random tree (RT), Linear regression (LR), M5P, and artificial neural network (ANN) have been looked out to predict the compressive strength of concrete mixed with marble powder. Assessment of result suggests that, the overall performance of ANN based model gives preferable results over the different applied algorithms for the estimate of compressive strength of concrete. The results of coefficient of correlation were maximum in ANN model (0.9139) accompanied through RT with coefficient of correlation (CC) value 0.8241 and minimum root mean square error (RMSE) value of ANN (4.5611) followed by RT with RMSE (5.4246). Similarly, other evaluating parameters like, Willmott's index and Nash-sutcliffe coefficient value of ANN was 0.9458 and 0.7502 followed by RT model (0.8763 and 0.6628). The end result showed that, for both subsets i.e., training and testing subset, ANN has the potential to estimate the compressive strength of concrete. Also, the results of sensitivity suggest that the water-cement ratio has a massive impact in estimating the compressive strength of concrete with marble powder with ANN based model in evaluation with the different parameters for this data set. | ||
| Key Words | ||
| artificial neural network; coefficient of correlation; compressive strength; marble powder; Nash-Sutcliffe coefficient; root mean square error; Willmott's index | ||
| Address | ||
| (1) Nitisha Sharma, Ankita Upadhya, Mohindra S. Thakur: Department of Civil Engineering, Shoolini University, Solan, Himachal Pradesh, 173229, India; (2) Parveen Sihag: Department of Civil Engineering, Chandigarh University, Ajitgarh, Punjab, 140413, India. | ||
