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Knowledge transfer for large-scale urban growth modeling based on formal concept analysis / Jinyao Lin in Transactions in GIS, vol 20 n° 5 (October 2016)  

Public [article]  inTransactions in GIS > vol 20 n° 5 (October 2016) . - pp 684 – 700 Titre : Knowledge transfer for large-scale urban growth modeling based on formal concept analysis Type de document : Article/Communication Auteurs : Jinyao Lin, Auteur ; Xia Li, Auteur Année de publication : 2016 Article en page(s) : pp 684 – 700 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] automate cellulaire [Termes IGN] croissance urbaine [Termes IGN] découverte de connaissances [Termes IGN] étalonnage des données [Termes IGN] Kouangtoung (Chine) [Termes IGN] modèle conceptuel de données localisées [Termes IGN] modélisation spatiale Résumé : (auteur) Cellular automata (CA) are useful for studies on urban growth and land-use changes. Although various methods have been developed to define transition rules, modeling urban growth of large areas remains a tough challenge owing to heterogeneous geographical features. To address the problem, we present a novel method based on the combination of Formal Concept Analysis (FCA) and knowledge transfer techniques. FCA is used to solicit association rules among cities within a large area. This method can provide a theoretical basis for the knowledge transfer process. A cutting-edge algorithm called TrAdaBoost is then integrated with the commonly-used Logistic-CA as the modeling framework. The proposed method is applied to the urban growth modeling of Guangdong Province, a large region with 21 cities in China, from 2005 to 2008. Compared with traditional methods, this method can achieve better results at the provincial and local levels, according to the experiments. The combination of FCA and knowledge transfer is expected to provide a useful tool for calibrating large-scale urban CA models. Numéro de notice : A2016-997 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12172 En ligne : http://dx.doi.org/10.1111/tgis.12172 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83777 [article]