Proceedings. 12th International Conference on Scientific and Statistica Database Management
DOI: 10.1109/ssdm.2000.869794
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Generating network-based moving objects

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Cited by 344 publications
(439 citation statements)
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“…We use the Network-based Generator of Moving Objects [9] to generate a set of moving objects. The input to the generator is Figure 7.…”
Section: Resultsmentioning
confidence: 99%
“…We use the Network-based Generator of Moving Objects [9] to generate a set of moving objects. The input to the generator is Figure 7.…”
Section: Resultsmentioning
confidence: 99%
“…El autor demuestra, con los resultados de las pruebas realizadas, la validez del algoritmo desarrollado comparándolo con algunos de los algoritmos más utilizados (Dijkstra y A*) y, además, describe la aplicación de dicho algoritmo en un complemento creado para la herramienta SIG Quantum GIS (QGIS). Las pruebas descritas son realizadas sobre los datos propuestos en [33], [34], los cuales hacen referencia a ciudades o condados de América del Norte.…”
Section: Servicio Provincial De Rutas Para La Idercunclassified
“…Unique post-analysis techniques are proposed that use the trajectory density function to extract valuable knowledge to characterize spatial clusters. 4. The proposed methods are evaluated on synthetic tra c and real-world Atlantic hurricane datasets.…”
Section: A Novel Density-based Trajectory Clustering Algorithm Namedmentioning
confidence: 99%
“…Let C be a cluster, d intra (C) is the average intra cluster distance of C and ψ(C) is the average object density of cluster C, the density volume of cluster C is de ned as: (4) 4 Experimental evaluations In this section, we apply the methodologies described in section 3 to an arti cial tra c dataset and a hurricane dataset. We used Hausdor distance [1] as the distance function in the following experiments.…”
Section: Post Analysis For Trajectory Clustersmentioning
confidence: 99%