A neural qualitative approach for automatic territorial zoning.

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dc.contributorRENATO JOSE SANTOS MACIEL, CNPTIA; MARCOS AURELIO SANTOS DA SILVA, CPATC; UFS; MARCIA HELENA GALINA DOMPIERI, CPATC.
dc.creatorMACIEL, R. J. S.
dc.creatorSILVA, M. A. S. da
dc.creatorMATOS, L. N.
dc.creatorDOMPIERI, M. H. G.
dc.date2018-01-19T19:10:00Z
dc.date2018-01-19T19:10:00Z
dc.date2018-01-19
dc.date2017
dc.date2020-01-21T11:11:11Z
dc.date.accessioned2026-07-07T04:15:25Z
dc.descriptionThis article presents the application of the Self-Organizing Maps (SOM) as an exploratory tool for automatic territorial zoning by combining the handle of categorical data and the other for automatic clustering. The SOM online learning algorithm had been chosen to treat categorical data by using the dot product method and the Sorense-Dice binary similarity coefficient. To automatically perform a spatial clustering, an adaptation of the automatic clustering Costa-Netto algorithm had been also proposed. The correspondence analysis had been used to examine the profiles of each homogeneous zones. To explore the approach it has been performed the territorial zoning of the Alto Taquari River Basin, Brazil, using as input data a set of thematic maps. The results indicate the applicability of the approach to perform the exploratory territorial zoning.
dc.descriptionGeoComputation 2017.
dc.formatp. 1-7.
dc.identifierA neural qualitative approach for automatic territorial zoning. In: INTERNATIONAL CONFERENCE ON GEOCOMPUTATION, 21., 2017, Leeds. Celebrating 21 years of GeoComputation: extended abstracts. Leeds: University of Leeds, 2017.
dc.identifierhttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1085890
dc.identifier.urihttp://hdl.handle.net/123456789/455736
dc.languageeng
dc.rightsopenAccess
dc.subjectBacia do Alto Taquari
dc.subjectZoneamento
dc.subjectAnálise espacial
dc.subjectSelf-organizing maps
dc.subjectExploratory spatial analysis
dc.subjectSimilarity coefficients
dc.subjectAlto Taquari River Basin
dc.subjectCorrespondence analysis
dc.subjectZoning
dc.subjectThematic maps
dc.titleA neural qualitative approach for automatic territorial zoning.
dc.typeArtigo em anais e proceedings

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