%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