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Generalization-oriented road line classification by means of an artificial neural network / J.L. Garcia Balboa in Geoinformatica, vol 12 n° 3 (September - November 2008)  

Public [article]  inGeoinformatica > vol 12 n° 3 (September - November 2008) . - pp 289 - 312 Titre : Generalization-oriented road line classification by means of an artificial neural network Type de document : Article/Communication Auteurs : J.L. Garcia Balboa, Auteur ; Francisco Javier Ariza-López, Auteur Année de publication : 2008 Article en page(s) : pp 289 - 312 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] acquisition de connaissances [Termes IGN] analyse en composantes principales [Termes IGN] apprentissage dirigé [Termes IGN] axe médian [Termes IGN] classification par réseau neuronal [Termes IGN] généralisation cartographique automatisée [Termes IGN] matrice d'erreur [Termes IGN] objet géographique linéaire [Termes IGN] route [Termes IGN] segmentation [Vedettes matières IGN] Généralisation Résumé : (Auteur) In line generalization, a first goal to achieve is the classification of features previous to the selection of processes and parameters. A feed forward backpropagation artificial neural network (ANN) is designed for classifying a set of road lines through a supervised learning process, attempting to emulate a classification performed by a human expert for cartographic generalization purposes. The main steps of the process are presented in this paper: (a) experimental data selection; (b) segmentation of lines into homogeneous sections, (c) sections enrichment through a set of quantitative measures derived from a principal component analysis, and qualitative information derived from road network and road type; (d) expert classification of the sections; and finally (e) the ANN design, training and validation. The quality of results is analyzed by means of error matrices after a cross-validation process giving a goodness, or percentage of agreement, over 83%. Copyright Springer Numéro de notice : A2008-282 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1007/s10707-007-0026-z En ligne : https://doi.org/10.1007/s10707-007-0026-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29275 [article]

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057-08031	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Approximating cartography to the customer's expectations: applying the “House of Quality” to map design / Francisco Javier Ariza-López in Cartographica, vol 43 n° 2 (June 2008)  

Public [article]  inCartographica > vol 43 n° 2 (June 2008) . - pp 107 - 123 Titre : Approximating cartography to the customer's expectations: applying the “House of Quality” to map design Type de document : Article/Communication Auteurs : Francisco Javier Ariza-López, Auteur ; J.L. Garcia Balboa, Auteur Année de publication : 2008 Article en page(s) : pp 107 - 123 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Rédaction cartographique [Termes IGN] conception cartographique [Termes IGN] étude de marché [Termes IGN] indicateur de qualité [Termes IGN] qualité totale [Termes IGN] spécification de produit Résumé : (Auteur) The design of a map and guide for a Spanish natural park has been guided by the application of a product-development methodology known as quality function deployment (QFD). QFD is a tool for bringing the voice of the customer into the product-development process, from conceptual design to manufacturing. In order to develop a high-quality product whose design meets customers’ needs, market research has been developed to discover customers’ expectations and the strengths and weaknesses of competitors’ products. Sixteen main customer expectations (WHATs) were considered in relation to product comfort, content, and portrayal. In order to take into account the afore mentioned expectations, 24 technical descriptors (HOWs) were considered. The product was finally specified by all the technical descriptors and their target values (HOW MUCHs). Results of the methodology are expressed using a set of matrices that depicts a house, the “House of Quality,” that concentrates the most important aspects of a product plan. Applying this methodology is an enriching experience, but somewhat difficult and time consuming. Copyright University of Toronto Press Numéro de notice : A2008-216 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.3138/carto.43.2.107 En ligne : https://doi.org/10.3138/carto.43.2.107 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29211 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
031-08021	RAB	Revue	Centre de documentation	En réserve L003	Disponible