Decision-Aid Methods Based on Belief Function Theory with Application to Torrent Protection

Autor: Jean Dezert, Mireille Batton-Hubert, Simon Carladous, Jean-Marc Tacnet
Přispěvatelé: Office national des forêts (ONF), Erosion torrentielle neige et avalanches (UR ETGR (ETNA)), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), DTIS, ONERA, Université Paris Saclay (COmUE) [Palaiseau], ONERA-Université Paris Saclay (COmUE), École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT), Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), Département Génie mathématique et industriel (FAYOL-ENSMSE), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Institut Henri Fayol, Institut Henri Fayol (FAYOL-ENSMSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Bossé É., Rogova G., Office National des Forêts (ONF), Ecole Nationale Supérieure des Mines de St Etienne-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), Ecole Nationale Supérieure des Mines de St Etienne-Institut Henri Fayol, DTIS, ONERA, Université Paris Saclay [Palaiseau], ONERA-Université Paris-Saclay, Ecole Nationale Supérieure des Mines de St Etienne-Université Clermont Auvergne (UCA)-Centre National de la Recherche Scientifique (CNRS)
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Information Quality in Information Fusion and Decision Making. Information Fusion and Data Science
Bossé É., Rogova G. Information Quality in Information Fusion and Decision Making. Information Fusion and Data Science, Springer, Cham, pp.329-357, 2019, 978-3-030-03643-0. ⟨10.1007/978-3-030-03643-0_15⟩
Information Fusion and Data Science ISBN: 9783030036423
Information Quality in Information Fusion and Decision Making
Popis: International audience; In mountainous areas, decision-makers must find the best solution to protect elements-at-torrential risk. The decision process involves several criteria and is based on imperfect information. Classical Multi-Criteria Decision-Aiding methods (MCDAs) are restricted to precise criteria evaluation for decision-making under a risky environment and suffer of rank reversal problems. To bridge these gaps, several MCDAs have been recently developed within belief function theory framework. The aims of this chapter are to introduce how these methods can be applied in practice and to introduce their general principles. To show their applicability to the real-life problem, we apply them to the Decision-Making Problem (DMP) comprising the comparison of several protective alternatives against torrential floods and selection of the most efficient one. We finally discuss the method improvements to promote their practical implementation.
Databáze: OpenAIRE