ANALYSIS OF PERFORMANCE OF BACKPROPAGATION ANN WITH DIFFERENT TRAINING PARAMETERS. IN: NEURAL NETWORKS IN TRANSPORT APPLICATIONS

Three inputs to a typical backpropagation based artificial neural network (ANN) modelling procedure are the number of hidden units, the learning rate (LR), and the momentum constant (MC). These three inputs have a profound effect on the ANN training as well as the resulting behavior of a trained network. This paper follows research done for the purpose of modeling trip generation using regression analysis and ANNs. The paper first presents a brief introduction to the problem of trip generation, and then explains the database used for modeling. The results of backpropagation modeling are also presented, followed by conclusions and recommendations.

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  • Corporate Authors:

    Ashgate Publishing Company

    110 Cherry Street, Suite 3-1
    Burlington, VT  United States  05401-3818
  • Authors:
    • Faghri, A
    • Sandeep, A
  • Publication Date: 1998

Language

  • English

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Filing Info

  • Accession Number: 00796279
  • Record Type: Publication
  • ISBN: 184014808X
  • Files: TRIS
  • Created Date: Jul 25 2000 12:00AM