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From Conventional to Knowledge Based Geographical Information Systems

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  • Fischer, Manfred M.

Abstract

Artificial intelligence (Al) has received an explosion of interest during the last five years in various fields. There is no longer any question that expert systems and neural networks will be of central importance for developing the next generation of more intelligent geographic information systems. Such knowledge based geographic information systems will especially play a key role in spatial decision and policy analysis related to issues such as environmental monitoring and management, land use planning, motor vehicle navigation and distribution logistics. This paper sketches briefly the major characteristics of conventional geographic information systems, and then looks at some of the potentials of Al principles and techniques in a GIS environment where emphasis is laid on expert systems and artificial neural networks technologies and techniques.

Suggested Citation

  • Fischer, Manfred M., 1994. "From Conventional to Knowledge Based Geographical Information Systems," MPRA Paper 77817, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:77817
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    File URL: https://mpra.ub.uni-muenchen.de/77817/1/MPRA_paper_77817.pdf
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    References listed on IDEAS

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    1. 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.
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    Cited by:

    1. Georgia Pozoukidou, 2006. "Planning Support Systems' Application Bottlenecks," ERSA conference papers ersa06p769, European Regional Science Association.
    2. Tom Kauko, 2009. "Classification of Residential Areas in the Three Largest Dutch Cities Using Multidimensional Data," Urban Studies, Urban Studies Journal Limited, vol. 46(8), pages 1639-1663, July.

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    Keywords

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    JEL classification:

    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling

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