Normalization Methods on Backpropagation for the Estimation of Drivers' Route Choice

The artificial neural network has recently been applied in many areas including transport engineering and planning. Even though its successful application for wide transportation areas, there are some major issues to be considered before using the neural network models, such as the network topology,...

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Bibliographic Details
Published inKSCE journal of civil engineering Vol. 9; no. 5; pp. 403 - 406
Main Authors Kim, Kyung Whan, Kim, Daehyon, Jung, Hun Young
Format Journal Article
LanguageEnglish
Published Seoul 대한토목학회 01.09.2005
Springer Nature B.V
Subjects
Artificial neural networks
Back propagation networks
Methods
Network topologies
Neural networks
Route selection
Studies
Topology
Vectors
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Summary:The artificial neural network has recently been applied in many areas including transport engineering and planning. Even though its successful application for wide transportation areas, there are some major issues to be considered before using the neural network models, such as the network topology, learning parameter, and normalization methods for the input vectors. In this research, se veral normalization methods for input vectors were studied and the experimental results showed that the performance of the drier's ro ute choice model using the neural networks was dependent on the normalization methods. For the estimation of driver's route choice, the best normalization method in the Backpropagation neural network model was suggested in this study.
ISSN:1226-7988
1976-3808
DOI:10.1007/BF02830631