CINDEFI   05381
CENTRO DE INVESTIGACION Y DESARROLLO EN FERMENTACIONES INDUSTRIALES
Unidad Ejecutora - UE
artículos
Título:
Artificial neural network to predict the growth of Leptospirillum ferrooxidans in 9K defined medium
Autor/es:
LAVALLE A.; CURIA L.; LAVALLE L.,; GIAVENO A.,; DONATI E.R.
Revista:
International Journal of Engineering Research and Applications
Editorial:
IJERA
Referencias:
Año: 2012 vol. 2 p. 1406 - 1416
ISSN:
2248-9622
Resumen:
An artificial neural network (ANN) model was carried out to predict the cell concentration and ferrous iron concentration
in the growth of strains of Leptospirillum ferrooxidans in batch culture, at different temperatures and pH values. A custom
network with three interacting blocks was developed to carry out the prediction. The temperature, pH and time were fed as
inputs to the network. In each block, a Multi Layer Perceptron was used and a tapped delay line was added in the first block.
The appropriate architecture of the neural network model was determined through several steps of training and testing. The
final ANN model was found to provide an efficient and a robust tool in predicting two variables simultaneously, in complex
conditions such as non-linear and time-variant biological processes.