Radial basis function neural networks for modeling growth rates of the basidiomycetes Physisporinus vitreus and Neolentinus lepideus

@article{Schubert2009RadialBF,
  title={Radial basis function neural networks for modeling growth rates of the basidiomycetes Physisporinus vitreus and Neolentinus lepideus},
  author={Mark Schubert and Safer Mourad and Francis W. M. R. Schwarze},
  journal={Applied Microbiology and Biotechnology},
  year={2009},
  volume={85},
  pages={703-712}
}
A radial basis function (RBF) neural network was developed and compared against a quadratic response surface (RS) model for predicting the specific growth rates of the biotechnologically important basidiomycetous fungi, Physisporinus vitreus and Neolentinus lepideus, under three environmental conditions: temperature (10–30 °C), water activity (0.950–9.998), and pH (4–6). Both the RBF network and polynomial RS model were mathematically evaluated against experimental data using graphical plots… CONTINUE READING
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