Neural networks and regional science modeling: A survey of techniques for complex spatial analysis

Thomas G. Wier, Vir V. Phoha

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

This study examines the value of utilizing neural net modeling for issues relating to optimization across a network of cities in space. Neural nets are made up of many nonlinear computational elements that operate in parallel and are arranged in a manner similar to biological neural nets. Defining a neural net model involves specifying a net topology, arrangement of nodes, training or learning rules, adjustment of weights associated with connections, node characteristics, and rules of transformation from input to output. All of these are the major issues in such regional problems as labor force migration and firm location.

Original languageEnglish (US)
Pages (from-to)309-324
Number of pages16
JournalReview of Regional Studies
Volume32
Issue number2
StatePublished - Jun 1 2002
Externally publishedYes

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Earth-Surface Processes

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