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Principles of Neural Spatial Interaction Modeling

In: Tool Kits in Regional Science

Author

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  • Manfred M. Fischer

    (Vienna University of Economics and Business Administration)

Abstract

This chapter is intended as a convenient resource for regional scientists interested in a statistical view of the neural spatial interaction modelling approach. We view neural spatial interaction models as an example of non-parametric estimation that makes few, if any, a priori assumptions about the nature of the data-generating process to approximate the true, but unknown spatial interaction function of interest. We limit the scope of this chapter to unconstrained spatial interaction and use appropriate statistical arguments to gain important insights into the problems and properties of this modelling approach that may be useful for those interested in application development. The remainder of this chapter is structured as follows. The next section introduces the class of neural spatial interaction models of interest, and sets forth the context in which spatial interaction modelling will be considered. The sections that follow present important components of a methodology for neural spatial interaction modelling.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:adspcp:978-3-642-00627-2_8
    DOI: 10.1007/978-3-642-00627-2_8
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    References listed on IDEAS

    as
    1. Manfred M. Fischer & Katerina Hlavácková-Schindler & Martin Reismann, 1999. "articles: A global search procedure for parameter estimation in neural spatial interaction modelling," Papers in Regional Science, Springer;Regional Science Association International, vol. 78(2), pages 119-134.
    2. 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.
    3. Fischer, Manfred M. & Reismann, Martin, 2002. "A Methodology for Neural Spatial Interaction Modeling," MPRA Paper 77794, University Library of Munich, Germany.
    4. Manfred M. Fischer & Jinfeng Wang, 2011. "Spatial Data Analysis," SpringerBriefs in Regional Science, Springer, number 978-3-642-21720-3, March.
    5. Manfred M. Fischer, 2000. "Methodological Challenges in Neural Spatial Interaction Modelling: The Issue of Model Selection," Advances in Spatial Science, in: Aura Reggiani (ed.), Spatial Economic Science, chapter 6, pages 89-101, Springer.
    6. Manfred M Fischer & Martin Reismann & Katerina Hlavackova–Schindler, 2003. "Neural Network Modeling of Constrained Spatial Interaction Flows: Design, Estimation, and Performance Issues," Journal of Regional Science, Wiley Blackwell, vol. 43(1), pages 35-61, February.
    7. Fischer, Manfred M. & Gopal, Sucharita, 1994. "Artificial Neural Networks. A New Approach to Modelling Interregional Telecommunication Flows," MPRA Paper 77822, University Library of Munich, Germany.
    8. Manfred M. Fischer & Arthur Getis, 1999. "introduction: New advances in spatial interaction theory," Papers in Regional Science, Springer;Regional Science Association International, vol. 78(2), pages 117-118.
    9. Fischer, Manfred M & Nijkamp, Peter, 1992. "Geographic Information Systems and Spatial Analysis," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 26(1), pages 3-17, April.
    10. Manfred M. Fischer, 2002. "Learning in neural spatial interaction models: A statistical perspective," Journal of Geographical Systems, Springer, vol. 4(3), pages 287-299, October.
    11. Mozolin, M. & Thill, J. -C. & Lynn Usery, E., 2000. "Trip distribution forecasting with multilayer perceptron neural networks: A critical evaluation," Transportation Research Part B: Methodological, Elsevier, vol. 34(1), pages 53-73, January.
    12. Fischer, Manfred M. & Reismann, Martin & Hlavackova-Schindler, Katerina, 2000. "Evaluating Neural Spatial Interaction. Modelling By Bootstrapping," ERSA conference papers ersa00p370, European Regional Science Association.
    13. Manfred M. Fischer & Yee Leung, 1998. "A genetic-algorithms based evolutionary computational neural network for modelling spatial interaction data," ERSA conference papers ersa98p478, European Regional Science Association.
    14. Manfred M. Fischer & Martin Reismann, 2001. "Neural Network Modelling of Constrained Spatial Interaction Flows," ERSA conference papers ersa01p165, European Regional Science Association.
    15. Aura Reggiani (ed.), 2000. "Spatial Economic Science," Advances in Spatial Science, Springer, number 978-3-642-59787-9, Fall.
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