Modeling of Reinforcement in Concrete Beams Using Machine Learning Tools
| Main Author: | Yogesh Aggarwal |
|---|---|
| Format: | Article |
| Bahasa: | eng |
| Terbitan: |
, 2007
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/1082405 |
Daftar Isi:
- The paper discusses the results obtained to predict reinforcement in singly reinforced beam using Neural Net (NN), Support Vector Machines (SVM-s) and Tree Based Models. Major advantage of SVM-s over NN is of minimizing a bound on the generalization error of model rather than minimizing a bound on mean square error over the data set as done in NN. Tree Based approach divides the problem into a small number of sub problems to reach at a conclusion. Number of data was created for different parameters of beam to calculate the reinforcement using limit state method for creation of models and validation. The results from this study suggest a remarkably good performance of tree based and SVM-s models. Further, this study found that these two techniques work well and even better than Neural Network methods. A comparison of predicted values with actual values suggests a very good correlation coefficient with all four techniques.