Methods: The Model-Building Tool Kit

Chapter
Part of the SpringerBriefs in Geography book series (BRIEFSGEOGRAPHY)

Abstract

Probably as with all tool kits, there are different ways of assembling the elements, with different mixes, to tackle a particular task. We choose here to present the tools in three boxes. First we focus on account-based models. So many models are rooted in accounts—literally counting the elements of our systems of interest and how these numbers change—that this makes a good starting point. We have seen from the examples so far that we will usually use a discrete zone system with variables like Pi representing the population of a typical zone i and {Tij} or {Sij} representing interaction between zones. We will seek to draw on this kind of notation to illustrate the accounts as they are introduced. Secondly, we review the mathematical tools that are available to us. We note briefly a range of modelling styles which can be described as ‘generic’. These have often been applied in one field but can be applied more widely. We then, thirdly, review the basic mathematical methods that are available to us—essentially as an outline of a mathematics-for-modellers ‘catch-up’ course!

Keywords

Mathematical Programming Transportation Problem Demographic Model Spatial Interaction Model Retail Model 
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.

References

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Further Reading

  1. Artle R (1959) Studies in the structure of the Stockholm economy, the business research unit of the Stockholm school of economics. Cornell University Press, Ithaca, republished 2005Google Scholar
  2. Kim TJ, Boyce DE, Hewings GJD (1983) Combined input–output and commodity flow models for inter-regional development planning. Geog Anal 15:330–342CrossRefGoogle Scholar
  3. Rees PH, Wilson AG (1977) Spatial population analysis. Edward Arnold, LondonGoogle Scholar
  4. Rogers A (2008) Demographic modelling of migration and population: a multiregional perspective. Geog Anal 40:276–296CrossRefGoogle Scholar
  5. Stone R (1967) Mathematics in the social sciences. Chapman and Hall, LondonGoogle Scholar
  6. Stone R (1970) Mathematical models of the economy. Chapman and Hall, LondonGoogle Scholar
  7. Wilson AG (2006) Ecological and urban systems models: some explorations of similarities in the context of complexity theory. Environ Plan A 38:633–646CrossRefGoogle Scholar
  8. Wilson AG (1970) Entropy in urban and regional modelling. Pion, London, Chapter 3Google Scholar

Copyright information

© The Author(s) 2012

Authors and Affiliations

  1. 1.Centre for Advanced Spatial AnalysisUniversity College LondonLondonUK

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