Ontology is an important part of the W3C standards for the Semantic Web used to specify standard conceptual vocabularies to exchange data among systems, provide reusable knowledge bases, and facilitate interoperability across multiple heterogeneous systems and databases. However, current ontology is not sufficient for handling vague information that is commonly found in many application domains...

This contribution proposes a Genetic Algorithm for jointly performing a feature selection and granularity learning for Fuzzy RuleBased Classification Systems in the scenario of data-sets with a high imbalance degree. We refer to imbalanced data-sets when the class distribution is not uniform, a situation that it is present in many real application areas. The aim of this work is to get more comp...

In this contribution we present uniform goal-directed rules for the implicational fragments of the three main formalizations of fuzzy logic; namely, Łukasiewicz logic Ł, Gödel logic G, and Product logic Π. We begin with a historical overview of the goal-directed methodology, focussing in particular on the pioneering work of Dov Gabbay, then proceed by recalling the fundamental systems of fuzzy ...

quantifying spatial structure is one of the most important components, describing natural ecosystems and their biodiversity. in this study, a set of indices and functions related to spatial structure using 102 established plots with an area of 1000 m2 were presented. to achieve spatial structure of carpinus-fagus type, a set of indices (clark & evans, uniform angle, shannon-wiener, mingling and...

in this paper a network comprising alternative branching nodes with probabilistic outcomes is considered. in other words, network nodes are probabilistic with exclusive-or receiver and exclusive-or emitter. first, an analytical approach is proposed to simplify the structure of network. then, it is assumed that the duration of activities is positive trapezoidal fuzzy number (tfn). this paper com...

Some uniform categorical theoretical treatment of automata and lattice-valued fuzzy automata using quantale theory is studied in this paper. First, L-relational sheaves on a monoidM andQ-enriched categories are introduced for quantales L andQ, the equivalence of the corresponding categories are proved next. Then lattice-valued (fuzzy) automata are described by Q-enriched categories. In fact, la...

In this paper we present a generalization of belief functions over fuzzy events. In particular we focus on belief functions defined in the algebraic framework of finite MV-algebras of fuzzy sets. We introduce a fuzzy modal logic to formalize reasoning with belief functions on many-valued events. We prove, among other results, that several different notions of belief functions can be characteriz...

Hybrid systems composed of AI approaches have shown quite remarkable results in diagnosis. Designing of such multi-method sytems generally bears some diiculties in nding a uniform representation of inputs and outputs of their subsystems. Since Fuzzy Logic, too, has proven high importance in Artiicial Intelligence, due to its adequate pseudoverbal representation of knowledge, it is well suited t...

In this paper, a robust adaptive fuzzy backstepping control is developed for a class of strict-feedback canonical nonlinear systems. The systems may possess unknown functions, the nonlinear dynamic uncertainties and unmodeled dynamics. The fuzzy logic systems are used to approximate the unknown nonlinear functions and nonlinear damping terms are used to counteract the nonlinear dynamic uncertai...

This paper describes a new method to detect faces in color images based on the fuzzy theory. We make two fuzzy models to describe the skin color and hair color, respectively. In these models, we use a perceptually uniform color space to describe the color information to increase the accuracy and stableness. We use the two models to extract the skin color regions and the hair color regions, and ...