FACTORS INFLUENCING THE PERFORMANCE OF A NEURAL NETWORK DRIVER DECISION MODEL: A CASE STUDY USING SIMULATED DATA. IN: NEURAL NETWORKS IN TRANSPORT APPLICATIONS
Neural networks and artificial neural networks have been applied by researchers for a broad range of disciplines including traffic engineering. The background, functionality and application of an increasing selection of neural network paradigms or models is well documented. This paper uses a case study to demonstrate that simulated data can be used effectively in preliminary development of a model; this allows a more clearly defined approach to further development using observed site data.
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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:
- LYONS, G D
- Hunt, J G
- Yousif, S Y
- Publication Date: 1998
Language
- English
Media Info
- Features: Figures; References; Tables;
- Pagination: p. 229-248
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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: Artificial intelligence; Backpropagation; Decision making; Driver education; Model atmosphere; Neural networks; Simulation; Traffic control
- Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; Safety and Human Factors;
Filing Info
- Accession Number: 00796287
- Record Type: Publication
- ISBN: 184014808X
- Files: TRIS
- Created Date: Jul 26 2000 12:00AM