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Calculating the Effect of Neural Network Parameters on Their Performance

EasyChair Preprint no. 3298

6 pagesDate: April 30, 2020


In this research, a three-layer neuronal network was studied and designed, a network capable of learning a set of large data with the help of the reverse propagation error method, and studying the effect of parameter changes (learning step, number of nodes, type of activation dependent for a number of different income signals) and the severe impact This change in the work of the neural network causes it, as the results of these experiments demonstrated the extreme sensitivity of the designed neuron response, which relies on the propagation technique to change these parameters.

Keyphrases: algorithm instruction, Back propagation algorithm, layers, neural networks

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Manhal Basher Hasan Aga},
  title = {Calculating the Effect of Neural Network Parameters on Their Performance},
  howpublished = {EasyChair Preprint no. 3298},

  year = {EasyChair, 2020}}
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