@article{2268,
  author = {Abraham Antonio López Villarreal, Samuel González-López, Luis Arturo Medina Muñoz},
  title = {Planar Robot Arm Performance: Analysis with Feedforward Neural Networks},
  journal = {Journal of Networking Technology},
  year = {2017},
  volume = {8},
  number = {2},
  doi = {},
  url = {http://www.dline.info/jnt/fulltext/v8n2/jntv8n2_2.pdf},
  abstract = {The purpose of this paper is to define the best training algorithm and activation function during the training process of a two degree of freedom planar robot arm that can be used to approach SCARA applications. A feed-forward neural network with two hidden layers was trained with several training algorithms such as Levenberg-Marquardt, Bayesian Regularization and others, and the activation functions such as symmetric sigmoid, logarithmic sigmoid and linear transfer to compare the resulting error and look for optimal performance.},
}