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This paper is devoted to the problem of measuring similarity between pieces of uncertain (incomplete) information in the framework of I-fuzzy set theory (Atanassov's intuitionistic fuzzy sets and interval-valued fuzzy sets). We propose a way of determining an interval-valued similarity measure of I-fuzzy sets that preserves information about the operands' uncertainty by approximating lower and upper...
This paper presents a summarized characterization of embedded type-1 fuzzy sets (ET1FS) by using the classical concept of convex combination given by Zadeh. ET1FSs are important when defining the centroid of an interval-valued fuzzy set (IVFS) and some type-reduction methods proposed in the literature. We will show that any ET1FS of an IVFS, with no assumption whatsoever about the universal set (either...
This paper proposes a new belief structure fuzzy inference system (FIS) that can model vagueness, ambiguity and interval uncertainties in the knowledge base. The interval belief structure is introduced to define the rules of an FIS and build uncertain knowledge. Fuzzy implication followed by extended fuzzy Dempster-Shafer combination is presented for inference in the proposed rule-based system. The...
The evidential reasoning (ER) approach was developed to support multiple criteria decision analysis (MCDA). It is based on the Dampster's combination rule for criteria aggregation and belief function for treating ignorance. In the original ER approach, however, alternative ranking depends on the accurate estimation of a value function, which may be difficult in certain decision environments. In this...
In recent years, dealing with uncertainty using interval probabilities is receiving considerable attention by researchers. Most of researches related to interval probabilities, such as combination, marginalization, condition, Bayesian inferences, assume interval probabilities are known. How to elicit interval probabilities from subject is a basic problem for the applications of interval probability...
We present new techniques for establishing lower bounds in robot motion planning problems. Our scheme is based on path encoding and uses homotopy equivalence classes of paths to encode state. We first apply the method to the shortest path problem in 3 dimensions. The problem is to find the shortest path under an Lp metric (e.g. a euclidean metric) between two points amid polyhedral obstacles. Although...
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