Combining in situ flow cytometry and artificial neural networks for aquatic systems monitoring

  title={Combining in situ flow cytometry and artificial neural networks for aquatic systems monitoring},
  author={Gilberto Carvalho Pereira and Nelson F. F. Ebecken},
  journal={Expert Syst. Appl.},
In order to produce a system to automatically identify field water samples, it is essential to cover the entire spectrum of biological variation that a species can be found in the natural environments. This information must be available for modeling within specific training data sets. Thus, the one of the objectives of this work is to build a set of flow cytometric data containing this information in order to develop artificial neural network models that learn the patterns of biological… CONTINUE READING
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