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.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/184014808X
• 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
• 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