Francklin Rivas

TL;DR: In this article, the authors used both linear and quadratic discriminant analysis (QDA) and artificial neural networks (ANNs) trained with the backpropagation algorithm for estimating if beverages can be distinguished based on the concentrations of these elements in the final product, and whether it is possible to assess the geographic location of the manufacturers (Lara or Falcon states) and the presence or absence of sugar in the end product.

TL;DR: Artificial intelligence (AI) has been used for more than two decades as a development tool for solutions in several areas of the EP (e.g., workflow automation, automatic process control, rule-based case reasoning, data mining, proxy models, and virtual environments) as discussed by the authors.

TL;DR: A new approach to predict the degradation of bearings by a time series forecasting model called the neo-fuzzy neuron using the root mean square extracted from vibration signals as a health indicator is presented.

TL;DR: The present work was aimed at comparing the performance of two chemometric techniques and two artificial neural networks as screening tools for cancer, with the probabilistic neural network offered additional advantages when compared to the more popular backpropagation counterpart.