Descripteur
Termes IGN > informatique > génie logiciel > programmation informatique > programmation par contraintes
programmation par contraintesSynonyme(s)PpcVoir aussi |
Documents disponibles dans cette catégorie (149)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Resilient GNSS real-time kinematic precise positioning with inequality and equality constraints / Zhetao Zhang in GPS solutions, vol 27 n° 3 (July 2023)
[article]
Titre : Resilient GNSS real-time kinematic precise positioning with inequality and equality constraints Type de document : Article/Communication Auteurs : Zhetao Zhang, Auteur ; Yuan Li, Auteur ; Xiufeng He, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 116 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes IGN] contrainte d'intégrité
[Termes IGN] positionnement cinématique en temps réel
[Termes IGN] positionnement par GNSS
[Termes IGN] précision du positionnement
[Termes IGN] résolution d'ambiguïtéRésumé : (auteur) How to conduct the GNSS real-time kinematic precise positioning in challenging environments is not an easy problem. The challenging environment mainly refers to frequent signal reflection, refraction, diffraction, and occlusion, inevitably introducing large positioning errors. We propose a resilient positioning method considering the inequality and equality constraints. Specifically, first, we introduce the functional and stochastic models of real-time kinematic (RTK) positioning, considering the impacts of challenging environments. Second, specific iterative procedures of resilient GNSS precise positioning method with inequality and equality constraints are proposed. In addition, a general form of inequality constraints in terms of coordinate components is given that is suitable for real-time kinematic situations. Four 24-h real datasets in canyon environments were collected to verify the performance of the proposed method. The results show that compared with the traditional RTK positioning without inequality constraints, the proposed method can improve the success rates of ambiguity resolution by 42.2% on average. Also, the positioning accuracy of fixed solutions can be improved significantly after applying the proposed method, where the root mean square errors can be reduced by 77.2% on average. Therefore, the proposed method can significantly improve success rates of ambiguity resolution and positioning accuracy, which is especially promising in challenging environments. Numéro de notice : A2023-213 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-023-01454-0 Date de publication en ligne : 26/04/2023 En ligne : https://doi.org/10.1007/s10291-023-01454-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103142
in GPS solutions > vol 27 n° 3 (July 2023) . - n° 116[article]Graph neural networks with constraints of environmental consistency for landslide susceptibility evaluation / Haowei Zeng in International journal of geographical information science IJGIS, vol 36 n° 11 (November 2022)
[article]
Titre : Graph neural networks with constraints of environmental consistency for landslide susceptibility evaluation Type de document : Article/Communication Auteurs : Haowei Zeng, Auteur ; Qing Zhu, Auteur ; Yulin Ding, Auteur ; et al., Auteur Année de publication : 2022 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] aléa
[Termes IGN] cartographie des risques
[Termes IGN] cohérence des données
[Termes IGN] effondrement de terrain
[Termes IGN] prédiction
[Termes IGN] programmation par contraintes
[Termes IGN] réseau neuronal de graphes
[Termes IGN] vulnérabilitéRésumé : (auteur) In complex and heterogeneous geoenvironments, landslides exhibit varying features in different environments, and data in landslide inventories are imbalanced. Existing data-driven landslide susceptibility evaluation (LSE) methods overlook environmental heterogeneity and cannot reliably predict regions with few samples. Alternatively, global random negative sampling strategies may produce imbalanced positive and negative samples in some environments, contributing to inaccurate predictions. This article proposes a graph neural network (GNN) constrained by environmental consistency (GNN-EC) to overcome these problems. The GNN-EC consists of graphs with nodes, and edges. A graph represents the environmental relationships in the study area. Nodes are geographic units delineated from terrain polygon approximation. Edges capture the relationships between node-pairs. Additionally, the weights of edges reflect the similarity between two node environments. A GNN aggregates node information in the graph for LSE. Our experiment showed that the proposed method outperformed the common machine learning methods: increasing prediction accuracy by approximately 7, 5–6 and 3–4% compared to the artificial neural network (ANN), the support vector machine (SVM) and the random forest (RF), respectively. Moreover, our method can maintain high prediction accuracy, even with a small training set. Numéro de notice : A2022-626 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2022.2103819 Date de publication en ligne : 28/07/2022 En ligne : https://doi.org/10.1080/13658816.2022.2103819 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101396
in International journal of geographical information science IJGIS > vol 36 n° 11 (November 2022)[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 079-2022111 SL Revue Centre de documentation Revues en salle Disponible Polyline simplification based on the artificial neural network with constraints of generalization knowledge / Jiawei Du in Cartography and Geographic Information Science, Vol 49 n° 4 (July 2022)
[article]
Titre : Polyline simplification based on the artificial neural network with constraints of generalization knowledge Type de document : Article/Communication Auteurs : Jiawei Du, Auteur ; Jichong Yin, Auteur ; Chengyi Liu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 313 - 337 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] descripteur
[Termes IGN] données maillées
[Termes IGN] données vectorielles
[Termes IGN] généralisation cartographique automatisée
[Termes IGN] polyligne
[Termes IGN] programmation par contraintes
[Termes IGN] réseau neuronal artificiel
[Termes IGN] simplification de contour
[Vedettes matières IGN] GénéralisationRésumé : (auteur) The present paper presents techniques for polyline simplification based on an artificial neural network within the constraints of generalization knowledge. The proposed method measures polyline shape characteristics that influence polyline simplification using abstracted descriptors and then introduces these descriptors into the artificial neural network as input properties. In total, 18 descriptors categorized into three types are presented in detail. In a second approach, map simplification principles are abstracted as controllers, imposed after the output layer of the trained artificial neural network to make the polyline simplification comply with these principles. This study worked with three controllers – a basic controller and two knowledge-based controllers. These descriptors and controllers abstracted from generalization knowledge were tested in experiments to determine their efficacy in polyline simplification based on the artificial neural network. The experimental results show that the utilization of abstracted descriptors and controllers can constrain the artificial neural network-based polyline simplification according to polyline shape characteristics and simplification principles. Numéro de notice : A2022-479 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : https://doi.org/10.1080/15230406.2021.2013944 Date de publication en ligne : 17/01/2022 En ligne : https://doi.org/10.1080/15230406.2021.2013944 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100885
in Cartography and Geographic Information Science > Vol 49 n° 4 (July 2022) . - pp 313 - 337[article]Constraint-based evaluation of map images generalized by deep learning / Azelle Courtial in Journal of Geovisualization and Spatial Analysis, vol 6 n° 1 (June 2022)
[article]
Titre : Constraint-based evaluation of map images generalized by deep learning Type de document : Article/Communication Auteurs : Azelle Courtial , Auteur ; Guillaume Touya , Auteur ; Xiang Zhang, Auteur Année de publication : 2022 Projets : 2-Pas d'info accessible - article non ouvert / Article en page(s) : n° 13 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] apprentissage profond
[Termes IGN] connexité (graphes)
[Termes IGN] données d'entrainement (apprentissage automatique)
[Termes IGN] montagne
[Termes IGN] programmation par contraintes
[Termes IGN] qualité des données
[Termes IGN] rendu réaliste
[Termes IGN] route
[Vedettes matières IGN] GénéralisationRésumé : (auteur) Deep learning techniques have recently been experimented for map generalization. Although promising, these experiments raise new problems regarding the evaluation of the output images. Traditional map generalization evaluation cannot directly be applied to the results in a raster format. Additionally, the internal evaluation used by deep learning models is mostly based on the realism of images and the accuracy of pixels, and none of these criteria is sufficient to evaluate a generalization process. Finally, deep learning processes tend to hide the causal mechanisms and do not always guarantee a result that follows cartographic principles. In this article, we propose a method to adapt constraint-based evaluation to the images generated by deep learning models. We focus on the use case of mountain road generalization, and detail seven raster-based constraints, namely, clutter, coalescence reduction, smoothness, position preservation, road connectivity preservation, noise absence, and color realism constraints. These constraints can contribute to current studies on deep learning-based map generalization, as they can help guide the learning process, compare different models, validate these models, and identify remaining problems in the output images. They can also be used to assess the quality of training examples. Numéro de notice : A2022-449 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s41651-022-00104-2 Date de publication en ligne : 07/05/2022 En ligne : http://dx.doi.org/10.1007/s41651-022-00104-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100646
in Journal of Geovisualization and Spatial Analysis > vol 6 n° 1 (June 2022) . - n° 13[article]Clustering with implicit constraints: A novel approach to housing market segmentation / Xiaoqi Zhang in Transactions in GIS, vol 26 n° 2 (April 2022)
[article]
Titre : Clustering with implicit constraints: A novel approach to housing market segmentation Type de document : Article/Communication Auteurs : Xiaoqi Zhang, Auteur ; Yanqiao Zheng, Auteur ; Qiong Peng, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 585 - 608 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] algorithme glouton
[Termes IGN] analyse de groupement
[Termes IGN] Chine
[Termes IGN] classification par nuées dynamiques
[Termes IGN] contrainte topologique
[Termes IGN] hétérogénéité spatiale
[Termes IGN] logement
[Termes IGN] marché foncier
[Termes IGN] programmation par contraintes
[Termes IGN] segmentation
[Termes IGN] structure spatiale
[Termes IGN] zone urbaineRésumé : (auteur) Constrained clustering has been widely studied and outperforms both the traditional unsupervised clustering and experience-oriented approaches. However, the existing literature on constrained clustering concentrates on spatially explicit constraints, while many constraints in housing market studies are implicit. Ignoring the implicit constraints will result in unreliable clustering results. This article develops a novel framework for constrained clustering, which takes implicit constraints into account. Specifically, the research extends the classical greedy searching algorithm by adding one back-and-forth searching step, efficiently coping with the order sensitivity. Via evaluation on both synthetic and real data sets, it turns out that the proposed algorithm outperforms existing algorithms, even when only the traditional pairwise constraints are provided. In an application to a concrete housing market segmentation problem, the proposed algorithm shows its power to accommodate user-specified homogeneity criteria to extract hidden information on the underlying urban spatial structure. Numéro de notice : A2022-362 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1111/tgis.12878 Date de publication en ligne : 26/12/2021 En ligne : https://doi.org/10.1111/tgis.12878 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100581
in Transactions in GIS > vol 26 n° 2 (April 2022) . - pp 585 - 608[article]Road network generalization method constrained by residential areas / Zheng Lyu in ISPRS International journal of geo-information, vol 11 n° 3 (March 2022)PermalinkA constraint-based approach for identifying the urban–rural fringe of polycentric cities using multi-sourced data / Jing Yang in International journal of geographical information science IJGIS, vol 36 n° 1 (January 2022)PermalinkRecursive Gauss-Helmert model with equality constraints applied to the efficient system calibration of a 3D laser scanner / Sören Vogel in Journal of applied geodesy, vol 16 n° 1 (January 2022)PermalinkConstrained shortest path problems in bi-colored graphs: a label-setting approach / Amin AliAbdi in Geoinformatica, vol 25 n° 3 (July 2021)PermalinkLearning deep semantic segmentation network under multiple weakly-supervised constraints for cross-domain remote sensing image semantic segmentation / Yansheng Li in ISPRS Journal of photogrammetry and remote sensing, vol 175 (May 2021)PermalinkUsing geometric constraints to improve performance of image classifiers for automatic segmentation of traffic signs / Roholah Yazdan in Geomatica, vol 75 n° 1 (Mars 2021)PermalinkClustering et apprentissage profond sous contraintes pour l’analyse de séries temporelles : Application à l’analyse temporelle incrémentale en télédétection / Baptiste Lafabregue (2021)PermalinkUrban Wi-Fi fingerprinting along a public transport route / Guenther Retscher in Journal of applied geodesy, vol 14 n° 4 (October 2020)PermalinkLocal terrain modification method considering physical feature constraints for vector elements / Jiangfeng She in Cartography and Geographic Information Science, Vol 47 n° 5 (September 2020)PermalinkGeological map generalization driven by size constraints / Azimjon Sayidov in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)PermalinkSimultaneous intensity bias estimation and stripe noise removal in infrared images using the global and local sparsity constraints / Li Liu in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)PermalinkConstraint based evaluation of generalized images generated by deep learning / Azelle Courtial (2020)PermalinkKalman filtering with state constraints applied to multi-sensor systems and georeferencing / Sören Vogel (2020)PermalinkRealistic modeling of power transmission lines with geographic information systems / Joram Schito (2020)PermalinkSpatially constrained regionalization with multilayer perceptron / Michael Govorov in Transactions in GIS, Vol 23 n° 5 (October 2019)PermalinkReliable image matching via photometric and geometric constraints structured by Delaunay triangulation / San Jiang in ISPRS Journal of photogrammetry and remote sensing, vol 153 (July 2019)PermalinkEquivalent constraints for two-view geometry : Pose solution/pure rotation identification and 3D reconstruction / Qi Cai in International journal of computer vision, vol 127 n° 2 (February 2019)PermalinkQuery rewriting for semantic query optimization in spatial databases / Eduardo Mella in Geoinformatica, vol 23 n° 1 (January 2019)PermalinkGen*: a generic toolkit to generate spatially explicit synthetic populations / Kevin Chapuis in International journal of geographical information science IJGIS, vol 32 n° 5-6 (May - June 2018)PermalinkLRAGE : learning latent relationships with adaptive graph embedding for aerial scene classification / Yuebin Wang in IEEE Transactions on geoscience and remote sensing, vol 56 n° 2 (February 2018)PermalinkSimulation 3D de la constructibilité et utilisations pour l’aménagement [diaporama] / Mickaël Brasebin (2018)PermalinkTesting deformation hypotheses by constraints on a time series of geodetic observations / Hiddo Velsink in Journal of applied geodesy, vol 12 n° 1 (January 2018)PermalinkTraitement et analyse des contraintes urbaines pour une optimisation morphologique : Etude comparative des modèles MorVer et SimPLU3D / Alia Belkaid (2018)PermalinkDEM generation from contours and a low-resolution DEM / Xinghua Li in ISPRS Journal of photogrammetry and remote sensing, vol 134 (December 2017)PermalinkStructure from motion with line segments under relaxed endpoint constraints / Branislav Micusik in International journal of computer vision, vol 124 n° 1 (August 2017)PermalinkConstrained Palette-Space Exploration / Nicolas Mellado in ACM Transactions on Graphics, TOG, Vol 36 n° 4 (July 2017)PermalinkData-driven estimation of building interior plans / Julian F. Rosser in International journal of geographical information science IJGIS, vol 31 n° 7-8 (July - August 2017)PermalinkDIOGEN, a multi-level oriented model for cartographic generalization / Adrien Maudet in International journal of cartography, vol 3 n° 1 (June 2017)PermalinkMultilayer NMF for blind unmixing of hyperspectral imagery with additional constraints / L. Chen in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 4 (April 2017)PermalinkA spatial anomaly points and regions detection method using multi-constrained graphs and local density / Yan Shi in Transactions in GIS, vol 21 n° 2 (April 2017)PermalinkConstrained clustering by constraint programming / Thi-Bich-Hanh Dao in Artificial intelligence, vol 244 (March 2017)PermalinkMatching plot-level tree maps with 3D remote sensing data for assessing and estimating forest parameters / Cédric Vega (2017)PermalinkMise en place d’un processus de dessin automatisé de plans d’intérieurs à partir de nuages de points acquis par LIDAR / Léa Talec (2017)PermalinkCohérence logique dans les systèmes OLAP spatiaux : un état de l’art / Sandro Bimonte in Revue internationale de géomatique, vol 26 n° 1 (janvier - mars 2016)PermalinkFeature-driven generalization of isobaths on nautical charts: A multi-agent system approach / Eric Guilbert in Transactions in GIS, vol 20 n° 1 (February 2016)PermalinkRoutes visualization: Automated placement of multiple route symbols along a physical network infrastructure / Jules Teulade-Denantes in Journal of Spatial Information Science, JoSIS, n° 11 (September 2015)PermalinkInterferometric phase image estimation via sparse coding in the complex domain / Hao Hongxing in IEEE Transactions on geoscience and remote sensing, vol 53 n° 5 (mai 2015)PermalinkConstrained least squares algorithms for nonlinear unmixing of hyperspectral imagery / Hanye Pu in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)PermalinkFlexible building primitives for 3D building modeling / B. Xiong in ISPRS Journal of photogrammetry and remote sensing, vol 101 (March 2015)PermalinkRank-based strategies for cleaning inconsistent spatial databases / Nieves R. Brisaboa in International journal of geographical information science IJGIS, vol 29 n° 2 (February 2015)PermalinkDetection and correction of inconsistencies between river networks and contour data by spatial constraint knowledge / Tinghua Ai in Cartography and Geographic Information Science, Vol 42 n° 1 (January 2015)PermalinkPermalinkMulti-view 3D circular target reconstruction with uncertainty analysis / Bahman Soheilian in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 (September 2014)PermalinkA general framework for trajectory data warehousing and visual OLAP / Luca Leonardi in Geoinformatica, vol 18 n° 2 (April 2014)PermalinkFiltering airborne lidar data by modified white top-hat transform with directional edge constraints / Yong Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 2 (February 2014)Permalink