Fuzzy Interval Analysis

By Didier Dubois, Etienne E. Kerre, Radko Mesiar, Henri Prade. 2000

313 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/fa28ebe19e34764faced2b5ac6b554dd14b19f5e

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In Artificial Intelligence

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Citations in the corpus

A possibilistic programming approach for closed-loop supply chain network design under uncertainty (2010, unknown): “[43].”
The role of fuzzy sets in decision sciences: Old techniques and new directions (2011, methodology): “There are many ranking methods surveyed elsewhere [11, 56].”
Fuzzy scheduling: Modelling flexible constraints vs. coping with incomplete knowledge (2003, background): “…case, when some values appear more plausible than others, the natural extension of an interval is a fuzzy interval (Dubois and Prade, 1980, 1988; Dubois et al., 2000), that is, a possibility distribution representing more or less plausible values, viewed as a nested family of confidence…”
Possibility Theory, Probability Theory and Multiple-Valued Logics: A Clarification (2001, background): “• Zadeh’s [86] approximate reasoning methodology which tries to translate sets of sentences in natural languages into soft constraints on a frame of discernment, • fuzzy interval analysis [30] where uncertainty is represented by the possibilistic counterpart of random variables.”
Possibility theory and statistical reasoning (2006, background): “A fuzzy interval [26] is a possibility distribution on the real line whose cuts are (generally closed) intervals.”
Probability-Possibility Transformations, Triangular Fuzzy Sets, and Probabilistic Inequalities (2004, background): “It thus provides a graded generalisation of interval calculus [4].”
Linear programming with fuzzy parameters: An interactive method resolution (2007, methodology): “There are several methods to do this (see i.e. Dubois et al., 2000).”