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Integrating multi-agent evacuation simulation and multi-criteria evaluation for spatial allocation of urban emergency shelters / Jia Yu in International journal of geographical information science IJGIS, vol 32 n° 9-10 (September - October 2018)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 32 n° 9-10 (September - October 2018) . - pp 1884 - 1910 Titre : Integrating multi-agent evacuation simulation and multi-criteria evaluation for spatial allocation of urban emergency shelters Type de document : Article/Communication Auteurs : Jia Yu, Auteur ; Chuanrong Zhang, Auteur ; Jiahong Wen, Auteur ; Weidong Li, Auteur ; Rui Liu, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 1884 - 1910 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] agent (intelligence artificielle) [Termes descripteurs IGN] analyse multicritère [Termes descripteurs IGN] Shanghai (Chine) [Termes descripteurs IGN] simulation [Termes descripteurs IGN] système multi-agents [Termes descripteurs IGN] urgence [Termes descripteurs IGN] ville Résumé : (Auteur) The timely and secure evacuation of residents to nearby urban emergency shelters is of great importance during unexpected disaster events. However, evacuation and allocation of shelters are seldom examined as a whole, even though they are usually closely related tasks in disaster management. To conduct better spatial allocation of emergency shelters in cities, this study proposes a new method which integrates techniques of multi-agent system and multi-criteria evaluation for spatial allocation of urban emergency shelters. Compared with the traditional emergency shelter allocation methods, the proposed method highlights the importance of dynamic emergency evacuation simulations for spatial allocation suitability analysis. Three kinds of agents involved in evacuation and sheltering procedures are designed: government agents, shelter agents, and resident agents. Emergency evacuations are simulated based on the interactions of these agents to find potential problems, for example, time-consuming evacuation processes and road congestion. A case study in Jing’an District, Shanghai, China was conducted to demonstrate the feasibility of the proposed method. After three rounds of simulation and optimization, new shelters were spatially allocated and a detailed recommended plan of shelters and related facilities was generated. The optimized spatial allocation of shelters may help local residents to be evacuated more quickly and securely. Numéro de notice : A2018-307 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1463442 date de publication en ligne : 25/04/2018 En ligne : https://doi.org/10.1080/13658816.2018.1463442 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90451 [article]

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Video event recognition and anomaly detection by combining gaussian process and hierarchical dirichlet process models / Michael Ying Yang in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 4 (April 2018)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 84 n° 4 (April 2018) . - pp 203 - 214 Titre : Video event recognition and anomaly detection by combining gaussian process and hierarchical dirichlet process models Type de document : Article/Communication Auteurs : Michael Ying Yang, Auteur ; Wentong Liao, Auteur ; Yanpeng Cao, Auteur ; Bodo Rosenhahn, Auteur Année de publication : 2018 Article en page(s) : pp 203 - 214 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] agent (intelligence artificielle) [Termes descripteurs IGN] apprentissage non-dirigé [Termes descripteurs IGN] approche hiérarchique [Termes descripteurs IGN] image vidéo [Termes descripteurs IGN] modèle de Markov [Termes descripteurs IGN] modèle orienté agent [Termes descripteurs IGN] séquence d'images Résumé : (Auteur) In this paper, we present an unsupervised learning framework for analyzing activities and interactions in surveillance videos. In our framework, three levels of video events are connected by Hierarchical Dirichlet Process (HDP) model: low-level visual features, simple atomic activities, and multi-agent interactions. Atomic activities are represented as distribution of low-level features, while complicated interactions are represented as distribution of atomic activities. This learning process is unsupervised. Given a training video sequence, low-level visual features are extracted based on optic flow and then clustered into different atomic activities and video clips are clustered into different interactions. The HDP model automatically decides the number of clusters, i.e., the categories of atomic activities and interactions. Based on the learned atomic activities and interactions, a training dataset is generated to train the Gaussian Process (GP) classifier. Then, the trained GP models work in newly captured video to classify interactions and detect abnormal events in real time. Furthermore, the temporal dependencies between video events learned by HDP-Hidden Markov Models (HMM) are effectively integrated into GP classifier to enhance the accuracy of the classification in newly captured videos. Our framework couples the benefits of the generative model (HDP) with the discriminant model (GP). We provide detailed experiments showing that our framework enjoys favorable performance in video event classification in real-time in a crowded traffic scene. Numéro de notice : A2018-139 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.84.4.203 date de publication en ligne : 01/04/2018 En ligne : https://doi.org/10.14358/PERS.84.4.203 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89689 [article]

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DIOGEN, a multi-level oriented model for cartographic generalization / Adrien Maudet in International journal of cartography, vol 3 n° 1 (June 2017)  

Public [article]  inInternational journal of cartography > vol 3 n° 1 (June 2017) . - pp 121 - 133 Titre : DIOGEN, a multi-level oriented model for cartographic generalization Type de document : Article/Communication Auteurs : Adrien Maudet, Auteur ; Guillaume Touya , Auteur ; Cécile Duchêne , Auteur ; Sébastien Picault, Auteur Année de publication : 2017 Article en page(s) : pp 121 - 133 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] AGENT [Termes descripteurs IGN] agent (intelligence artificielle) [Termes descripteurs IGN] CartACom [Termes descripteurs IGN] carte thématique [Termes descripteurs IGN] contrainte relationnelle [Termes descripteurs IGN] DIOGEN [Termes descripteurs IGN] données vectorielles [Termes descripteurs IGN] GAEL [Termes descripteurs IGN] généralisation cartographique automatisée [Termes descripteurs IGN] modèle (conceptuel) de généralisation [Termes descripteurs IGN] programmation par contraintes [Termes descripteurs IGN] système multi-agents [Vedettes matières IGN] Généralisation Résumé : (Auteur) Among approaches for automated generalization of vector data, we focus on the multi-agent paradigm: cartographic objects are modeled as agents (autonomous objects) that apply generalization algorithms to themselves to satisfy cartographic constraints. Several agent levels are considered, for example, individual agents, such as a building, and agents representing a group of agents, such as an urban block composed of the surrounding roads and contained buildings. Several multi-agent models were proposed to automate the orchestration of map generalization processes. Existing multi-agent generalization models have different approaches to manage the relations between agent levels. In this paper, we unify existing models, adapting a multi-level simulation model, to simplify interactions between agents in different levels. We propose the DIOGEN model, in which the principle of interactions between agents of different levels is adapted to constraint-driven cartographic generalization. DIOGEN unifies three existing multi-agent generalization models (AGENT, CartACom and GAEL), combine their behaviors and take advantage of their skills. Our proposal is evaluated on different use cases: instances of topographic mapping, and mapping of hiking routes over topographic data as an example of thematic mapping. Numéro de notice : A2017-321 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2017.1300997 date de publication en ligne : 20/04/2017 En ligne : http://dx.doi.org/10.1080/23729333.2017.1300997 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85379 [article]

Modelling a dynamic forest fuelmarket focusing on wood chips: a spatial agent-based approach to simulate competition among heating plants in the province of Carinthia, Austria / Johannes Scholz in GI Forum, vol 2017 n° 1 ([01/01/2017])  

Public [article]  inGI Forum > vol 2017 n° 1 [01/01/2017] . - pp 383 - 396 Titre : Modelling a dynamic forest fuelmarket focusing on wood chips: a spatial agent-based approach to simulate competition among heating plants in the province of Carinthia, Austria Type de document : Article/Communication Auteurs : Johannes Scholz, Auteur ; Florian Breitwieser, Auteur ; Peter Mandl, Auteur Année de publication : 2017 Article en page(s) : pp 383 - 396 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes descripteurs IGN] agent (intelligence artificielle) [Termes descripteurs IGN] Autriche [Termes descripteurs IGN] biomasse (combustible) [Termes descripteurs IGN] marché du bois [Termes descripteurs IGN] modèle orienté agent [Termes descripteurs IGN] modélisation spatio-temporelle [Termes descripteurs IGN] simulation dynamique Résumé : (auteur) Sustainability and renewable resources are attracting increased attention in the energy supply sector. This paper elaborates on the application of agent-based modelling methods to simulate forest fuel markets and supply chains. More precisely, it aims to simulate the market for wood chips for heating purposes, based on a sustainable forest growth and yield model, in conjunction with cognitive agents that act in the market. In the agent-based model, three types of agents are defined: forest owners (supply), biomass heating plant (demand), and ‘traders’, connecting supply and demand. Forest enterprises can decide on forest operations based on the state of the forest fuel market – e.g. considering the price for wood chips. Each biomass heating plant has an associated ‘trader’ that tries to fulfil the demand for forest biomass while minimizing the transport distances and the cost for the wood chips. The paper discusses the results of a simulation scenario in the Province of Carinthia, Austria. The simulation results are analysed with respect to space and time concerning biomass transport distance, transport patterns and remaining biomass stock. Numéro de notice : A2017-872 Thématique : FORET/GEOMATIQUE Nature : Article DOI : 10.1553/giscience2017_01_s383 date de publication en ligne : 30/06/2017 En ligne : https://doi.org/10.1553/giscience2017_01_s383 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90393 [article]

An intelligent geospatial processing unit for image classification based on geographic vector agents (GVAs) / Kambiz Borna in Transactions in GIS, vol 20 n° 3 (June 2016)  

Public [article]  inTransactions in GIS > vol 20 n° 3 (June 2016) . - pp 368–381 Titre : An intelligent geospatial processing unit for image classification based on geographic vector agents (GVAs) Type de document : Article/Communication Auteurs : Kambiz Borna, Auteur ; Antoni B. Moore, Auteur ; Pascal Sirguey, Auteur Année de publication : 2016 Article en page(s) : pp 368–381 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] agent (intelligence artificielle) [Termes descripteurs IGN] analyse d'image orientée objet [Termes descripteurs IGN] classification automatique [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données vectorielles [Termes descripteurs IGN] image Ikonos [Termes descripteurs IGN] modèle orienté agent Résumé : (auteur) Spatial modeling methods usually use pixels and image objects as fundamental processing units to address real-world objects, geo-objects, in image space. To do this, both pixel-based and object-based approaches typically employ a linear two-staged workflow of segmentation and classification. Pixel-based methods segment a classified image to address geo-objects in image space. In contrast, object-based approaches classify a segmented image to identify geo-objects from raster datasets. These methods lack the ability to simultaneously integrate the geometry and theme of geo-objects in image space. This article explores Geographical Vector Agents (GVAs) as an automated and intelligent processing unit to directly address real-world objects in the process of remote sensing image classification. The GVA is a distinct type of geographic automata characterized by elastic geometry, dynamic internal structure, neighborhoods and their respective rules. We test this concept by modeling a set of objects on a subset IKONOS image and LiDAR DSM datasets without the setting parameters (e.g. scale, shape information), usually applied in conventional Geographic Object-Based Image Analysis (GEOBIA) approaches. The results show that the GVA approach achieves more than 3.5% improvement for correctness, 2% improvement for quality, although no significant improvement for completeness to GEOBIA, thus demonstrating the competitive performance of GVAs classification. Numéro de notice : A2016-460 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : http://dx.doi.org/10.1111/tgis.12226 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81390 [article]

Modelling the spatial evolution of map objects by map agents / Shen Ying in Geocarto international, vol 31 n° 3 - 4 (March - April 2016)  

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Towards process validation for complex transport models: A sensitivity analysis of a social network-enhanced activity-travel model / Nicole Ronald in Computers, Environment and Urban Systems, vol 55 (January 2016)  

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Modélisation d’accompagnement en gestion conservatoire : Expérimentation au sein du réseau français Natura 2000 / Hélène Dupont in Revue internationale de géomatique, vol 25 n° 4 (octobre - décembre 2015)  

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Simuler les évolutions urbaines à l'aide de données géographiques urbaines 3D / Mickaël Brasebin in Revue internationale de géomatique, vol 24 n° 2 (juin - août 2014)  

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JFSMA'14 systèmes multi-agents : principe de parcimonie, 8-10 octobre 2014, Loriol-sur-Drôme / Rémy Courdier (2014)  

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Simulating spatial dynamics and processes in a retail gasoline market: An agent-based modeling approach / Alison J. Heppenstall in Transactions in GIS, vol 17 n° 5 (October 2013)  

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Modeling and communicating the conceptual intent of geo-analytical tasks for human-GIS interaction / G. Cai in Transactions in GIS, vol 17 n° 3 (June 2013)  

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Assessing the effect of landscape change on fauna by agent-based model simulation / Laurence Jolivet (2013)  

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Interactions between levels in an agent oriented model for generalisation / Adrien Maudet (2013) 

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JFSMA'13, vingt-et-unièmes journées francophones sur les systèmes multi-agents / Salima Hassas (2013)

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