Modelling spatial interaction using a neural net

  • Stan Openshaw


Neurocomputing has the potential to revolutionise many areas of urban and regional modelling by providing a general purpose systems modelling tool in applications where data exist. This chapter examines the empirical performance of a feedforward neural net as the basis for representing the spatial interaction contained within journey to work data. The performance of the neural net representation is compared with various types of conventional model. It is concluded that there is considerable potential for many more neural net applications in this and related areas.


Spatial Interaction Neural Computing Bidirectional Associative Memory Spatial Interaction Model Quantitative Geography 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • Stan Openshaw
    • 1
  1. 1.School of GeographyLeeds UniversityLeedsUK

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