Creating efficient nonlinear neural network process models that allow model interpretation

@inproceedings{Scott1993CreatingEN,
  title={Creating efficient nonlinear neural network process models that allow model interpretation},
  author={Gary M. Scott and W. Harmon Ray},
  year={1993}
}
Abstract The KBANN (knowledge-based artificial neural networks) approach uses neural networks to refine knowledge that can be written in the form of simple propositional rules. This idea is extended by presenting the MANNIDENT (multivariable artificial neural network identification) algorithm by which the mathematical equations of linear process models determine the topology and initial weights of a network, which is further trained using backpropagation. This method is applied to the task of… CONTINUE READING

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