0957-4174/$ see front matter 2008 Elsevier Ltd. A doi:10.1016/j.eswa.2008.04.001 * Corresponding author. E-mail address: [email protected] (C.H. Aladag A given observation in time series does not only depend on preceding one but also previous ones in general. Therefore, high order fuzzy time series approach might obtain better forecasts than does first order fuzzy time series approach. Definin...

Uncertainty is present in virtually all replacement decisions due to unknown future events, such as revenue streams, maintenance costs, and in°ation. Fuzzy sets provide a mathematical framework for explicitly incorporating imprecision into the decision-making model, especially when the system involves human subjectivity. This chapter illustrates the use of fuzzy sets and possibility theory to e...

The TSK model introduced by Takagi Sugeno and Kang TSK fuzzy reasoning is associated with fuzzy rules that have a special format with a func tional type consequent instead of the fuzzy consequent that normally appears in the MamdamiModel In this way the TSK approach tries to decompose the input space into subspaces and then approximate the system in each subspace by a simple linear regression m...

Fuzzy spaces are obtained by quantizing adjoint orbits of compact semi-simple Lie groups. Fuzzy spheres emerge from quantizing S and are associated with the group SU(2) in this manner. They are useful for regularizing quantum field theories and modeling spacetimes by non-commutative manifolds. We show that fuzzy spaces are Hopf algebras and in fact have more structure than the latter. They are ...

We give new sharp bounds for the number of generators for fuzzy ideals The pioneering works of Zadeh and Rosenfeld led to the fuzzi cation of algebraic structures Liu introduced and examined the notion of a fuzzy ideal of a ring Malik and Mordeson have been studying properties of fuzzy ideals see for example and The concept of minimal generating systems for fuzzy ideals was introduced in It has...

Stability of a fuzzy control system is closely related to the analytical structure of the fuzzy controller, which is determined by its components such as input and output fuzzy sets and fuzzy rules. We first characterize the mathematical input–output structure of fuzzy controllers and then utilize the structure characteristics to advance stability analysis. We study how the components of a gene...

The Simpliied Adaptive Resonance Theory (SART) class of networks is proposed to handle problems encountered in Adaptive Resonance Theory 1 (ART 1)-based algorithms when detection of binary and analog patterns is performed. The basic idea of SART is to substitute ART 1-based \unidirectional" (asymmetric) activation and match functions with \bidirectional" (symmetric) function pairs. This substit...

The rapid growth of the Internet and the expansion of electronic commerce applications in manufacturing have given rise to electronic customer relationship management (e-CRM) which enhances the overall customer satisfaction. However, when confronted by the range of e-CRM methods, manufacturing companies struggle to identify the one most appropriate to their needs. This paper presents a novel st...

By the development of Semantic Web, increasing demands for vague and distributed information representation have triggered a mass of theoretical and applied researches of fuzzy and distributed ontologies, whose main logical infrastructures are fuzzy and distributed description logics. However, current solutions are proposed respectively on one of these two aspects. By integrating E -connection ...

In this paper, a fuzzy modeling method using genetic algorithms (GAs) with a conciseness measure is presented. This paper introduces De Luca and Termini's fuzzy entropy to evaluate the shape of a membership function, and proposes another measure to evaluate the deviation of a membership function from symmetry. A combined measure is then derived from these two measures, and a new conciseness mea...