Communities detection algorithm to minimize risk during an evacuation

Autor: Antoine Dutot, Damien Olivier, Cyrille Bertelle, Pascal Mallet, Michel Nabaa
Přispěvatelé: Equipe Réseaux d'interactions et Intelligence Collective (RI2C - LITIS), Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes (LITIS), Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Université Le Havre Normandie (ULH), Normandie Université (NU)-Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Normandie Université (NU), CODAH, COmmunauté de l'Agglomération Havraise
Rok vydání: 2010
Předmět:
Zdroj: 2010 4th Annual IEEE Systems Conference
2010 4th Annual IEEE Systems Conference, Apr 2010, San Diego, France. pp.323-328, ⟨10.1109/SYSTEMS.2010.5482442⟩
Popis: Recent dramatic events recall to the world that is has to deal with risk problematic. Thus, to face risk in an agglomeration, we study hazards from natural or anthropic origin. One problem is to decide if it is necessary to evacuate or confine population. To help decision makers, we analyze the road network structure which may influence flow fluidity especially in a dangerous case. In this work, we detail an algorithm to detect communities in large graphs. It allows to identify routes that may cause problems in an evacuation case. Thanks to this algorithm, we study a toxic cloud propagation in a given zone and identify roads to avoid when evacuating this zone
Databáze: OpenAIRE