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Combinatorial optimization applied to VLBI scheduling / A. Corbin in Journal of geodesy, vol 94 n°2 (February 2020)  

Public [article]  inJournal of geodesy > vol 94 n°2 (February 2020) Titre : Combinatorial optimization applied to VLBI scheduling Type de document : Article/Communication Auteurs : A. Corbin, Auteur ; B. Niedermann, Auteur ; Axel Nothnagel, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes descripteurs IGN] analyse combinatoire (maths) [Termes descripteurs IGN] données VGOS [Termes descripteurs IGN] interférométrie à très grande base [Termes descripteurs IGN] positionnement par ITGB [Termes descripteurs IGN] programmation linéaire [Termes descripteurs IGN] retard troposphérique zénithal [Termes descripteurs IGN] station VLBI [Termes descripteurs IGN] téléscope [Termes descripteurs IGN] temps universel coordonné Résumé : (auteur) Due to the advent of powerful solvers, today linear programming has seen many applications in production and routing. In this publication, we present mixed-integer linear programming as applied to scheduling geodetic very-long-baseline interferometry (VLBI) observations. The approach uses combinatorial optimization and formulates the scheduling task as a mixed-integer linear program. Within this new method, the schedule is considered as an entity containing all possible observations of an observing session at the same time, leading to a global optimum. In our example, the optimum is found by maximizing the sky coverage score. The sky coverage score is computed by a hierarchical partitioning of the local sky above each telescope into a number of cells. Each cell including at least one observation adds a certain gain to the score. The method is computationally expensive and this publication may be ahead of its time for large networks and large numbers of VLBI observations. However, considering that developments of solvers for combinatorial optimization are progressing rapidly and that computers increase in performance, the usefulness of this approach may come up again in some distant future. Nevertheless, readers may be prompted to look into these optimization methods already today seeing that they are available also in the geodetic literature. The validity of the concept and the applicability of the logic are demonstrated by evaluating test schedules for five 1-h, single-baseline Intensive VLBI sessions. Compared to schedules that were produced with the scheduling software sked, the number of observations per session is increased on average by three observations and the simulated precision of UT1-UTC is improved in four out of five cases (6 μs average improvement in quadrature). Moreover, a simplified and thus much faster version of the mixed-integer linear program has been developed for modern VLBI Global Observing System telescopes. Numéro de notice : A2020-153 Thématique : MATHEMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-020-01348-w date de publication en ligne : 29/01/2020 En ligne : https://doi.org/10.1007/s00190-020-01348-w Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94786 [article]

Automatic reconstruction of fully volumetric 3D building models from oriented point clouds / Sebastian Ochmann in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 151 (May 2019) . - pp 251 - 262 Titre : Automatic reconstruction of fully volumetric 3D building models from oriented point clouds Type de document : Article/Communication Auteurs : Sebastian Ochmann, Auteur ; Richard Vock, Auteur ; Reinhard Klein, Auteur Année de publication : 2019 Article en page(s) : pp 251 - 262 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] Industry foudation classes IFC [Termes descripteurs IGN] modélisation 3D du bâti BIM [Termes descripteurs IGN] positionnement en intérieur [Termes descripteurs IGN] programmation linéaire [Termes descripteurs IGN] reconstruction 3D du bâti [Termes descripteurs IGN] semis de points Résumé : (Auteur) We present a novel method for reconstructing parametric, volumetric, multi-story building models from unstructured, unfiltered indoor point clouds with oriented normals by means of solving an integer linear optimization problem. Our approach overcomes limitations of previous methods in several ways: First, we drop assumptions about the input data such as the availability of separate scans as an initial room segmentation. Instead, a fully automatic room segmentation and outlier removal is performed on the unstructured point clouds. Second, restricting the solution space of our optimization approach to arrangements of volumetric wall entities representing the structure of a building enforces a consistent model of volumetric, interconnected walls fitted to the observed data instead of unconnected, paper-thin surfaces. Third, we formulate the optimization as an integer linear programming problem which allows for an exact solution instead of the approximations achieved with most previous techniques. Lastly, our optimization approach is designed to incorporate hard constraints which were difficult or even impossible to integrate before. We evaluate and demonstrate the capabilities of our proposed approach on a variety of complex real-world point clouds. Numéro de notice : A2019-210 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.03.017 date de publication en ligne : 30/03/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.03.017 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92676 [article]

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Excel data analysis / Hector Guerrero (2019)  

Public Titre : Excel data analysis : modeling and simulation Type de document : Guide/Manuel Auteurs : Hector Guerrero, Auteur Mention d'édition : 2ème édition Editeur : Springer Nature Année de publication : 2019 Importance : 358 p. ISBN/ISSN/EAN : 978-3-030-01279-3 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Statistiques [Termes descripteurs IGN] analyse de données [Termes descripteurs IGN] données qualitatives [Termes descripteurs IGN] Excel (logiciel) [Termes descripteurs IGN] inférence statistique [Termes descripteurs IGN] méthode de Monte-Carlo [Termes descripteurs IGN] programmation linéaire Résumé : (Editeur) This book offers a comprehensive and readable introduction to modern business and data analytics. It is based on the use of Excel, a tool that virtually all students and professionals have access to. The explanations are focused on understanding the techniques and their proper application, and are supplemented by a wealth of in-chapter and end-of-chapter exercises. In addition to the general statistical methods, the book also includes Monte Carlo simulation and optimization. The second edition has been thoroughly revised: new topics, exercises and examples have been added, and the readability has been further improved. The book is primarily intended for students in business, economics and government, as well as professionals, who need a more rigorous introduction to business and data analytics – yet also need to learn the topic quickly and without overly academic explanations. Note de contenu : 1. Introduction to Spreadsheet Modeling 2. Presentation of Quantitative Data: Data Visualization 3. Analysis of Quantitative Data 4. Presentation of Qualitative Data—Data Visualization 5. Analysis of Qualitative Data 6. Inferential Statistical Analysis of Data 7. Modeling and Simulation: Part 1 8. Modeling and Simulation: Part 2 9. Solver, Scenarios, and Goal Seek Tools Numéro de notice : 26280 Thématique : INFORMATIQUE/MATHEMATIQUE Nature : Manuel informatique DOI : 10.1007/978-3-030-01279-3 En ligne : https://doi.org/10.1007/978-3-030-01279-3 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94931

Un algorithme pour battre le record du SwissTrainChallenge : poser le pied dans chacun des 26 cantons le plus rapidement possible en utilisant uniquement des transports publics / Emmanuel Cledat in XYZ, n° 157 (décembre 2018 - février 2019)

Public [article]  inXYZ > n° 157 (décembre 2018 - février 2019) . - pp 30 - 36 Titre : Un algorithme pour battre le record du SwissTrainChallenge : poser le pied dans chacun des 26 cantons le plus rapidement possible en utilisant uniquement des transports publics Type de document : Article/Communication Auteurs : Emmanuel Cledat, Auteur ; Dirk Lauinger, Auteur Année de publication : 2018 Article en page(s) : pp 30 - 36 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications SIG [Termes descripteurs IGN] calcul d'itinéraire [Termes descripteurs IGN] chemin le plus rapide (algorithme) [Termes descripteurs IGN] connexité (graphes) [Termes descripteurs IGN] multilatération [Termes descripteurs IGN] programmation linéaire [Termes descripteurs IGN] réseau ferroviaire [Termes descripteurs IGN] Suisse [Termes descripteurs IGN] temps de trajet [Termes descripteurs IGN] train [Termes descripteurs IGN] transport public [Termes descripteurs IGN] vitesse Résumé : (auteur) The Swiss Train Challenge is to set foot in all 26 cantons of Switzerland in as little time as possible, using only public transportation. Relying on human intuition informed by a geographical information system to select the relevant train stations, and on computational power to solve the resulting mixed-integer linear optimization problem, we find a solution that beats the current record of 17 hours and 19 minutes, by 25 minutes. When testing our itinerary in practice, we made all connections but one for which the arriving train was 20 minutes delayed - a rare event in switzerland. This is the first time that an algorithm has been used to calculate the Swiss Train Challenge itinerary. Numéro de notice : A2018-532 Thématique : GEOMATIQUE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91577 [article]

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Object-based superresolution land-cover mapping from remotely sensed imagery / Yuehong Chen in IEEE Transactions on geoscience and remote sensing, vol 56 n° 1 (January 2018)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 56 n° 1 (January 2018) . - pp 328 - 340 Titre : Object-based superresolution land-cover mapping from remotely sensed imagery Type de document : Article/Communication Auteurs : Yuehong Chen, Auteur ; Yong Ge, Auteur ; Gerard B.M. Heuvelink, Auteur ; Ru An, Auteur ; Yu Chen, Auteur Année de publication : 2018 Article en page(s) : pp 328 - 340 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] classification orientée objet [Termes descripteurs IGN] classification pixellaire [Termes descripteurs IGN] déconvolution [Termes descripteurs IGN] krigeage [Termes descripteurs IGN] occupation du sol [Termes descripteurs IGN] programmation linéaire [Termes descripteurs IGN] variogramme Résumé : (Auteur) Superresolution mapping (SRM) is a widely used technique to address the mixed pixel problem in pixel-based classification. Advanced object-based classification will face a similar mixed phenomenon-a mixed object that contains different land-cover classes. Currently, most SRM approaches focus on estimating the spatial location of classes within mixed pixels in pixel-based classification. Little if any consideration has been given to predicting where classes spatially distribute within mixed objects. This paper, therefore, proposes a new object-based SRM strategy (OSRM) to deal with mixed objects in object-based classification. First, it uses the deconvolution technique to estimate the semivariograms at target subpixel scale from the class proportions of irregular objects. Then, an area-to-point kriging method is applied to predict the soft class values of subpixels within each object according to the estimated semivariograms and the class proportions of objects. Finally, a linear optimization model at object level is built to determine the optimal class labels of subpixels within each object. Two synthetic images and a real remote sensing image were used to evaluate the performance of OSRM. The experimental results demonstrated that OSRM generated more land-cover details within mixed objects than did the traditional object-based hard classification and performed better than an existing pixel-based SRM method. Hence, OSRM provides a valuable solution to mixed objects in object-based classification. Numéro de notice : A2018-186 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2747624 date de publication en ligne : 20/09/2017 En ligne : https://doi.org/10.1109/TGRS.2017.2747624 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89843 [article]

Robust minimum volume simplex analysis for hyperspectral unmixing / Shaoquan Zhang in IEEE Transactions on geoscience and remote sensing, vol 55 n° 11 (November 2017)  

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Linking ecosystem services with state-and-transition models to evaluate rangeland management decisions / Sapana Lohani in Global ecology and conservation, vol 8 (October 2016)  

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Recursive orthogonal projection-based simplex growing algorithm / Hsiao-Chi Li in IEEE Transactions on geoscience and remote sensing, vol 54 n° 7 (July 2016)  

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Gestion de collecte des déchets post-inondation / Oumayma Kaabi (2016)

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Probabilistic multi-person localisation and tracking / Tobias Klinger (2016) 

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Minimum volume simplex analysis: A fast algorithm for linear hyperspectral unmixing / Jun Li in IEEE Transactions on geoscience and remote sensing, vol 53 n° 9 (September 2015)  

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A comparative analysis of traveling salesman solutions from geographic information systems / Kevin M. Curtin in Transactions in GIS, vol 18 n° 2 (April 2014)  

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Attraction-repulsion model-based subpixel mapping of multi-/hyperspectral imagery / Xiaohua Tong in IEEE Transactions on geoscience and remote sensing, vol 51 n° 5 Tome 1 (May 2013)  

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Sampling piecewise convex unmixing and endmember extraction / Alina Zare in IEEE Transactions on geoscience and remote sensing, vol 51 n° 3 Tome 2 (March 2013)  

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Triangular factorization-based simplex algorithms for hyperspectral unmixing / W. Xia in IEEE Transactions on geoscience and remote sensing, vol 50 n° 11 Tome 1 (November 2012)  

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