Abstract
AOI(Attribute-Oriented Induction) is one of the data mining techniques with which phenomena of complicated spatial relationships can be expressed as specific rules by summarizing spatial or non-spatial data in accordance with super ordinate concepts. In addition to such AOI technique, if GIS(Geographic Information System) that has an advantage to solve space-related problems is combined, they can be used to expect the issues of urban growth. Combining the AOI technique and GIS, the study draws out spatial association rules focusing on a physical urban growth, and those rules are applied to urban growth models during the period from the 1960’s to the 1990’s. The results and analysis of the urban growth modes combined with data mining are compared with those of Clarke Keith’s UGM(Urban Growth Model).
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© 2007 Springer-Verlag Berlin Heidelberg
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Cho, S., Hong, S., Kim, J., Park, S. (2007). Design of Urban Growth Probability Model by Using Spatial Association Rules. In: Apolloni, B., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2007. Lecture Notes in Computer Science(), vol 4692. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74819-9_44
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DOI: https://doi.org/10.1007/978-3-540-74819-9_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74817-5
Online ISBN: 978-3-540-74819-9
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