IDEAS home Printed from https://ideas.repec.org/h/spr/adspcp/978-3-642-59787-9_17.html
   My bibliography  Save this book chapter

Feedforward Neural Networks for Spatial Interaction: Are They Trustworthy Forecasting Tools?

In: Spatial Economic Science

Author

Listed:
  • Jean-Claude Thill

    (State University of New York at Buffalo)

  • Mikhail Mozolin

    (ESRI, Inc.)

Abstract

Though it has often been criticized for providing too crude a rendition of processes underpinning revealed patterns of interaction between geo-referenced entities, spatial interaction modelling has persisted as one of the methodological pillars of several spatial sciences, including regional science, geography and transportation (Fotheringham and O’Kelly 1989; Ortuzar and Willumsen 1994; Sen and Smith 1995; Isard et al. 1998). Traditionally, the spatial interaction model is calibrated by one of several well known fitting and optimization techniques, including leastsquares regression, maximum likelihood, or by numerical heuristics.

Suggested Citation

  • Jean-Claude Thill & Mikhail Mozolin, 2000. "Feedforward Neural Networks for Spatial Interaction: Are They Trustworthy Forecasting Tools?," Advances in Spatial Science, in: Aura Reggiani (ed.), Spatial Economic Science, chapter 17, pages 355-381, Springer.
    • Handle: RePEc:spr:adspcp:978-3-642-59787-9_17
    DOI: 10.1007/978-3-642-59787-9_17
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Manfred M. Fischer, 2009. "Principles of Neural Spatial Interaction Modeling," Advances in Spatial Science, in: Michael Sonis & Geoffrey J. D. Hewings (ed.), Tool Kits in Regional Science, chapter 8, pages 199-214, Springer.
    2. Fischer, Manfred M. & Reismann, Martin, 2002. "A methodology for neural spatial interaction modelling," ERSA conference papers ersa02p034, European Regional Science Association.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:adspcp:978-3-642-59787-9_17. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.