Multi-criteria diagnosis of control knowledge for cartographic generalisation - Archive ouverte HAL
Article Dans Une Revue European Journal of Operational Research Année : 2012

Multi-criteria diagnosis of control knowledge for cartographic generalisation

Résumé

The development of interactive map websites increases the need of efficient automatic cartographic generalisation. The generalisation process, which aims at decreasing the level of details of geographic data in order to produce a map at a given scale, is extremely complex. A classical method for automating the generalisation process consists in using a heuristic tree-search strategy. This type of strategy requires having high quality control knowledge (heuristics) to guide the search for the optimal solution. Unfortunately, this control knowledge is rarely perfect and its evaluation is often difficult. Yet, this evaluation can be very useful to manage knowledge and to determine when to revise it. The objective of our work is to offer an automatic method for evaluating the quality of control knowledge for cartographic generalisation based on a heuristic tree-search strategy. Our diagnosis method consists in analysing the system's execution logs, and in using a multi-criteria analysis method for evaluating the knowledge global quality. We present an industrial application as a case study using this method for building block generalisation and this experiment shows promising results.
Fichier principal
Vignette du fichier
article_EJOR_-_perso.pdf (1.04 Mo) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-00688354 , version 1 (17-04-2012)

Identifiants

Citer

Patrick Taillandier, Franck Taillandier. Multi-criteria diagnosis of control knowledge for cartographic generalisation. European Journal of Operational Research, 2012, 217 (3), pp.633-642. ⟨10.1016/j.ejor.2011.10.004⟩. ⟨hal-00688354⟩
132 Consultations
179 Téléchargements

Altmetric

Partager

More