Uncertainty and imprecision accompany the world we live in and occur in almost every
event. How to better interpret and manage uncertainty and imprecision play a vital role in …

Increasingly we rely on machine intelligence for reasoning and decision making under
uncertainty. This tutorial reviews the prevalent methods for model-based autonomous …

We consider uncertain data which uncertainty is represented by belief functions and that
must be combined. The result of the combination of the belief functions can be partially …

In classification of incomplete pattern, the missing values can either play a crucial role in the
class determination, or have only little influence (or eventually none) on the classification …

Dempster-Shafer evidence theory is a primary methodology for multisource information
fusion because it is good at dealing with uncertain information. This theory provides a …

In the belief function theory, the concept of conflict appearing while confronting several
expertspsila opinions can serve for many purposes, and in particular it can be used as an …

Received signal strength (RSS) is a simple and low-cost method of localization in wireless
sensor networks (WSNs) and is of significant interest in ambient intelligence technologies …

Recent research in algorithms for solving global optimization problems using response
surface methodology has shown that it is in general not possible to use one surrogate model …

The classification of incomplete patterns is a very challenging task because the object
(incomplete pattern) with different possible estimations of missing values may yield distinct …

In this chapter, we present and discuss a new generalized proportional conflict redistribution
rule. The Dezert-Smarandache extension of the Dempster-Shafer theory has relaunched the …