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A neural network-based method for solving "nested hierarchy" areal interpolation problems / D. Merwin in Cartography and Geographic Information Science, vol 36 n° 4 (October 2009)  

Public [article]  inCartography and Geographic Information Science > vol 36 n° 4 (October 2009) . - pp 347 - 365 Titre : A neural network-based method for solving "nested hierarchy" areal interpolation problems Type de document : Article/Communication Auteurs : D. Merwin, Auteur ; R. Cromley, Auteur ; Daniel L. Civco, Auteur Année de publication : 2009 Article en page(s) : pp 347 - 365 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Statistiques [Termes IGN] analyse comparative [Termes IGN] Connecticut (Etats-Unis) [Termes IGN] figuration de la densité [Termes IGN] interpolation par pondération de zones [Termes IGN] interpolation spatiale [Termes IGN] prévision [Termes IGN] recensement démographique [Termes IGN] régression linéaire [Termes IGN] réseau neuronal artificiel [Termes IGN] structure hiérarchique de données Résumé : (Auteur) This study proposes a neural network approach to solving areal interpolation scenarios, specifically the “nested hierarchy” problem. The neural network method presented adopts the approach taken by intelligent interpolation methods where ancillary spatial information is presented to assist in achieving more accurate results. For this study, the data to be estimated are total populations for census tracts and block groups in Hartford County, Connecticut. A number of neural network models are generated containing various combinations of ancillary spatial information. The neural-network-derived predictions are compared with the predicted populations derived from three existing interpolation methods: areal weighting, a dasymetric areal weighting approach using remote sensing data, and ordinary least squares (OLS) regression. For each scenario presented, the proposed neural network approach outperforms each of the existing methods. Numéro de notice : A2009-441 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE Nature : Article DOI : 10.1559/152304009789786335 En ligne : https://doi.org/10.1559/152304009789786335 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30072 [article]

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