Scholarly Research Excellence
@article{(International Science Index):,
  title    = {Modeling of Reinforcement in Concrete Beams Using Machine Learning Tools},
  author    = {Yogesh Aggarwal},
  country   = {India},
  institution={National Institute of Technology, Kurukshetra},
  abstract  = {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.},
    journal   = {International Journal of Civil, Environmental, Structural, Construction and Architectural Engineering},  volume    = {1},
  number    = {8},
  year      = {2007},
  pages     = {69 - 73},
  ee        = {},
  url       = {},
  bibsource = {},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 8, 2007},