ENSMSE DEMO

Saint-Étienne, France

ENSMSE DEMO

Saint-Étienne, France
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Carladous S.,IRSTEA | Carladous S.,ONERA | Tacnet J.-M.,IRSTEA | Dezert J.,Xi'an Jiaotong University | And 2 more authors.
FUSION 2016 - 19th International Conference on Information Fusion, Proceedings | Year: 2016

Decision-Aid Methods (DAMs) such as the Cost-Benefit Analysis (CBA) and the Analytical Hierarchy Process (AHP) help decision-makers to rank alternatives or to choose the best one among several potential ones. The new Belief Function based Technique for Order Preference by Similarity to Ideal Solution (BF-TOPSIS) methods have been recently developed for Multi-Criteria Decision-Making problems. In this paper, we compare CBA, AHP and BF-TOPSIS methods through an actual application case to natural risks in mountains. The CBA is the most used approach but is limited. Classical Multi-Criteria Decision-Aid methods (MCDAs) such as the AHP help to go further. The BF-TOPSIS methods notably show a robustness to rank reversal problems in the problem under concern, with a tractable complexity. Moreover, some steps of these new methods can be included in other MCDAs developed under the belief function theory framework. © 2016 ISIF.


Carladous S.,IRSTEA | Carladous S.,Agro ParisTech | Tacnet J.-M.,IRSTEA | Dezert J.,The French Aerospace Laboratory | And 2 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2016

Experts take into account several criteria to assess the effectiveness of torrential flood protection systems. In practice, scoring each criterion is imperfect. Each system is assessed choosing a qualitative class of effectiveness among several such classes (high, medium, low, no). Evidential Reasoning for Multi-Criteria Decision-Analysis (ER-MCDA) approach can help formalize this Multi-Criteria Decision- Making (MCDM) problem but only provides a coarse ranking of all systems. The recent Belief Function-based Technique for Order Preference by Similarity to Ideal Solution (BF-TOPSIS) methods give a finer ranking but are limited to perfect scoring of criteria. Our objective is to provide a coarse and a finer ranking of systems according to their effectiveness given the imperfect scoring of criteria. Therefore we propose to couple the two methods using an intermediary decision and a quantification transformation step. Given an actual MCDM problem, we apply the ER-MCDA and its coupling with BF-TOPSIS, showing that the final fine ranking is consistent with a previous coarse ranking in this case. © Springer International Publishing Switzerland 2016.


Carladous S.,IRSTEA | Carladous S.,Agro ParisTech | Tacnet J.-M.,IRSTEA | Dezert J.,The French Aerospace Laboratory | And 2 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2016

The Evidential Reasoning for Multi Criteria Decision Analysis (ER-MCDA) is based on a mapping process transforming a possibility distribution into a Bayesian basic belief assignment (BBA) related to a qualitative frame of discernement (FoD). Each element of the FoD is a fuzzy set. A new improved mapping method is proposed to get a final potentially non-Bayesian BBA on the FoD. We apply it to assess the stability of protective check dams against torrential floods given their imprecise scouring rate. © Springer International Publishing Switzerland 2016.

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