Statistical techniques were developed for extracting the most significant features (indicators) from a transit system database, and classifying proposed and existing transit systems according to the selected features. The database was constructed by using information from all previous years available by the Mn/DOT, the Census and other sources to be used in classifying transit systems. The database emphasized the use of raw characteristics of the operating system and the area socioeconomics. The feature extraction was done so that the minimum number of features were extracted that can be used for classifying the transit systems with maximum accuracy. The classification method was designed around the database at minimum cost. The transit system patterns, resulting from the classification method, were identified according to need and performance, and the main characteristics were specified for each pattern. These characteristics and descriptions identifying each pattern determine whether it should be modified. A controlled experiment was required to test the classification method. A randomly selected part of the data was classified by the method, and then the unselected data was treated as a control group for the experiment. After the experiment a percent of misclassifications was calculated.

  • Corporate Authors:

    University of Minnesota, Minneapolis

    Department of Civil and Mineral Engineering, 122 Civil and Mineral Engineering Building
    Minneapolis, MN  United States  55455-0220

    Minnesota Department of Transportation

    Transportation Building, 395 John Ireland Boulevard
    St Paul, MN  United States  55155
  • Authors:
    • Spephanedes, Y J
  • Publication Date: 1990


  • English

Media Info

  • Features: Appendices; Figures; References; Tables;
  • Pagination: 159 p.

Subject/Index Terms

Filing Info

  • Accession Number: 00666434
  • Record Type: Publication
  • Source Agency: Federal Transit Administration
  • Report/Paper Numbers: MN-RC-94-17
  • Created Date: Sep 28 1994 12:00AM