• DocumentCode
    1791744
  • Title

    Multiway Analysis of bridge structural types in the National Bridge Inventory (NBI): A tensor decomposition approach

  • Author

    Adarkwa, Offei ; Schumacher, Ton ; Attoh-Okine, Nii

  • Author_Institution
    Dept. of Civil & Environ. Eng., Univ. of Delaware, Newark, DE, USA
  • fYear
    2014
  • fDate
    27-30 Oct. 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The National Bridge Inventory (NBI) has detailed information on over 600,000 bridges nationwide. The data, which spans a period of more than 20 years can be very useful for analyzing and modeling bridge performance. Previous analysis methods employ a 2-dimensional view of data which may result in the loss of subtle trends and changes in the data. Bridge data is inherently multidimensional and as such there is an added advantage in analyzing it in its natural multidimensional state. This paper focuses on the use of a multiway data analysis approach known as tensor decomposition to analyze the structural deficiency rate with respect to states, bridge structural types and time. The tensor decomposition approach is able to reveal clusters and patterns which are not easily perceptible when using conventional statistical tools.
  • Keywords
    bridges (structures); data analysis; structural engineering computing; tensors; NBI; bridge structural types; data changes; data trends; multiway data analysis approach; national bridge inventory; statistical tools; structural deficiency rate analysis; tensor decomposition; two-dimensional data view; Bridges; Data analysis; Loading; Market research; Slabs; Structural beams; Tensile stress; Bridges; Data Analysis; Multiway Data; Tensors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data (Big Data), 2014 IEEE International Conference on
  • Conference_Location
    Washington, DC
  • Type

    conf

  • DOI
    10.1109/BigData.2014.7004423
  • Filename
    7004423