%0 Journal Article
	%A Yogesh Aggarwal
	%D 2007
	%J International Journal of Civil and Environmental Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 8, 2007
	%T Modeling of Reinforcement in Concrete Beams Using Machine Learning Tools
	%U https://publications.waset.org/pdf/14131
	%V 8
	%X 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.
	%P 69 - 73