Mountain river torrents and snow avalanches generate human and material damages with dramatic consequences. Knowledge about natural phenomenona is often lacking and expertise is required for decision and risk management purposes using multi-disciplinary quantitative or qualitative approaches. Expertise is considered as a decision process based on imperfect information coming from more or less r...

This chapter defines and implements a non-Bayesian fusion rule for combining densities of probabilities, derived from imprecise knowledge. This rule is the restriction to a strict probabilistic paradigm of the Proportional Conflict Redistribution rule no 6 (PCR6) developed in the DSmT framework for fusing basic belief assignments. A sampling method for probabilistic PCR6 (p-PCR6) is defined. It...

The spatial prediction of land cover at the field scale in winter appears useful for the issue of bare soils reduction in agricultural intensive regions. High variability of the factors that motivate the land cover changes between each winter involves integration of uncertainty in the modelling process. Fusion process with Dempster-Shafer Theory (DST) presents some limits in generating errors i...

This paper presents a general method for combining uncertain and paradoxical source of evidences for a wide class of fusion problems. From the foundations of the Dezert-Smarandache Theory (DSmT) we show how the DSm rule of combination can be adapted to take into account all possible integrity constraints (if any) of the problem under consideration due to the true nature of elements/concepts inv...

The present paper contributes to the modeling of unsteady flow analysis of vertical axis wind turbine (VAWT). Double multiple stream tube (DSMT) model was applied for the performance prediction of straight bladed fixed pitch VAWT using NACA0018 airfoil at low wind speed. A moving mesh technique was used to investigate two-dimensional unsteady flow around the same VAWT model with NACA0018 airfoi...

Over the years, there have been many proposed methods in set-based tracking. One example of set-based methods is the use of Dempster-Shafer (DS) techniques to support belief-function (BF) tracking. In this paper, we overview the issues and concepts that motivated DS methods for simultaneous tracking and classification/identification. DS methods have some attributes, if applied correctly; but th...

In many applications involving epistemic uncertainties usually modeled by belief functions, it is often necessary to approximate general (non-Bayesian) basic belief assignments (BBAs) to subjective probabilities (called Bayesian BBAs). This necessity occurs if one needs to embed the fusion result in a system based on the probabilistic framework and Bayesian inference (e.g. tracking systems), or...

Scope of this paper is to investigate the performances of different identity declaration fusion algorithms in terms of probability of correct classification, supposing that the information for combination of the inferences from the different classifier is affected by measurement errors. In particular, these information have been assumed to be provided in the form of confusion matrices. Six iden...

Our results demonstrated the ability of the Free DezertSmarandache (DSm) model to improve thematic classification of forest regeneration over the use of Dempster-Shafer Theory (DST) and a classical Maximum Likelihood Algorithm (MLA). Overall, a classification accuracy of 82.75% was obtained with the reference method, MLA but it was improved by 7.4% by applying the fusion method DST (90.14%). Fu...

A combination handwritten signature veri ̄cation system is proposed for managing con°icts provided from each individual o®-line and on-line support vector machine (SVM), respectively. Basically, the system is divided into three parts: (i) O®-line veri ̄cation system, (ii) on-line veri ̄cation system and (iii) combination module using belief function theory. The proposed framework allows combining ...