COMPUTATIONAL NEURAL NETWORKS: AN ATTRACTIVE CLASS OF MATHEMATICAL MODELS FOR TRANSPORTATION RESEARCH. IN: NEURAL NETWORKS IN TRANSPORT APPLICATIONS

Most transportation research techniques and methods currently in use were developed in the 1960s and 1970s, in an era of scarce computing power and small data sets. Today, transportation research is entering a period of rapid change, a period which presents a unique opportunity for new styles of data analysis in order to meet the new needs for efficiently and comprehensively exploring large databases for patterns and relationships against a background of data uncertainty and noise, especially when the underlying database is of order of gigabytes. This paper argues that computational intelligence technologies in general and computational neural networks in particular show the potential for a new paradigm in transportation research providing transportation researchers with rich and interesting classes of novel data driven methods and techniques applicable to a wide range of domains in transportation research.

• 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:
  • Fischer, M M
• Publication Date: 1998

Language

• English

Media Info

• Features: Figures; References; Tables;
• Pagination: p. 3-20
• Serial:
  • Atmospheric Environment
  • Publisher: Elsevier
  • ISSN: 1352-2310
  • Serial URL: http://www.sciencedirect.com/science/journal/13522310

Subject/Index Terms

• TRT Terms: Artificial intelligence; Computer networks; Computer science; Mathematical models; Neural networks; Research; Telecommunications; Transportation
• Subject Areas: Planning and Forecasting; Research; Transportation (General);

Filing Info

• Accession Number: 00796277
• Record Type: Publication
• ISBN: 184014808X
• Files: TRIS
• Created Date: Jul 25 2000 12:00AM