A hybrid Bayesian-neural network approach for probabilistic modeling of bacterial growth/no-growth interface.

@article{Hajmeer2003AHB,
  title={A hybrid Bayesian-neural network approach for probabilistic modeling of bacterial growth/no-growth interface.},
  author={Maha N Hajmeer and Imad Basheer},
  journal={International journal of food microbiology},
  year={2003},
  volume={82 3},
  pages={233-43}
}
A hybrid probabilistic modeling approach that integrates artificial neural networks (ANNs) with statistical Bayesian conditional probability estimation is proposed. The suggested approach benefits from the power of ANNs as highly flexible nonlinear mapping paradigms, and the Bayes' theorem for computing probabilities of bacterial growth with the aid of Parzen's probability distribution function estimators derived for growth and no-growth (G/NG) states. The proposed modeling approach produces… CONTINUE READING

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