NEURAL NETWORKS AS ADAPTIVE LOGIT MODELS. IN: NEURAL NETWORKS IN TRANSPORT APPLICATIONS
Artificial neural networks (ANN), or neural networks (NN) have become increasingly popular over the last few years. ANNs have been applied to a variety of problems in transportation engineering, including pavement maintenance, vehicle detection/classification, traffic pattern analysis and traffic control. There have been fewer applications in the area of transportation economics and policy. This paper will demonstrate a unique connection between the multilayer feedforward neural network model and the binary logit model, where the former may be classified as a logit model without the restriction of linearity in the parameters in the utility function.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/184014808X
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Corporate Authors:
Ashgate Publishing Company
110 Cherry Street, Suite 3-1
Burlington, VT United States 05401-3818 -
Authors:
- Schintler, L A
- Olurotimi, O
- Publication Date: 1998
Language
- English
Media Info
- Features: Appendices; Figures; References;
- Pagination: p. 131-150
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Serial:
- Atmospheric Environment
- Publisher: Elsevier
- ISSN: 1352-2310
- Serial URL: http://www.sciencedirect.com/science/journal/13522310
Subject/Index Terms
- TRT Terms: Adaptive control; Artificial intelligence; Economics; Feedforward control; Logits; Model atmosphere; Neural networks; Regression analysis; Transportation policy
- Subject Areas: Data and Information Technology; Economics; Highways; Planning and Forecasting; Policy;
Filing Info
- Accession Number: 00796282
- Record Type: Publication
- ISBN: 184014808X
- Files: TRIS
- Created Date: Jul 25 2000 12:00AM