Logic rules and membership functions are two key components of a fuzzy logic controller (FLC). If only one component is learned, the other one is often set subjectively thus can reduce the applicability of FLC. If both components are learned simultaneously, a very long chromosome is often needed thus may deteriorate the learning performance. To avoid these shortcomings, this paper employs genet...

We study the problem of reconstructing binary images from four projections data in a fuzzy environment. Given the uncertainly projections,w e want to find a binary image that respects as best as possible these projections. We provide an iterative algorithm based on fuzzy integer programming and linear membership functions.

One of the main challenges for transportation engineers is the consideration of pedestrian safety as the most vulnerable aspect of the transport system. In many countries around the world, a large number of accidents recorded by the police are composed of accidents involving pedestrians and vehicles, for example when pedestrians may be struck by passing vehicles when crossing the street. Carefu...

In principle, we can have many different membership functions. Interestingly, however, in many practical applications, triangular and trapezoidal membership functions are the most efficient ones. In this paper, we use fuzzy approach to explain this empirical phenomenon.

In fuzzy models, redundancy may be present in the form of similar fuzzy sets, especially in the construction of a fuzzy system from a set of given training examples. In this paper, a simple formula for calculating the degree of similarity of Trapezoidal membership functions is derived in order to merge similar membership functions and hence to obtain a more transparent rule-base with a minimum ...

In this paper we present, propose and examine additional membership functions for the Smoothing Transition Autoregressive (STAR) models. More specifically, we present the tangent hyperbolic, Gaussian and Generalized bell functions. Because Smoothing Transition Autoregressive (STAR) models follow fuzzy logic approach, more fuzzy membership functions should be tested. Furthermore, fuzzy rules can...

The translation of knowledge contained in databank into linguistically interpretable fuzzy rules has proven in real applications to be difficult. A solution to this problem is furnished by multiresolution techniques. A dictionary of functions forming a multiresolution is used as candidate membership functions. The membership functions are chosen among the family of scaling functions that have t...

Caused by many applications during the last few years, many models have been proposed to represent imprecise and uncertain data. These models are essentially based on the theory of the theory of fuzzy sets, the theory of possibilities and the theory of belief functions. These two first theories are based on the membership functions and the last one on the belief functions. Hence, it could be in...

We consider a model of learning Boolean functions from quantum membership queries. This model was studied in [26], where it was shown that any class of Boolean functions which is information-theoretically learnable from polynomially many quantum membership queries is also information-theoretically learnable from polynomially many classical membership queries. In this paper we establish a strong...

In this paper, a maximum likelihood estimation and a minimum entropy estimation for the expected value and variance of normal fuzzy variable are discussed within the framework of credibility theory. As an application, a credibilistic portfolio selection model is proposed, which is an improvement over the traditional models as it only needs the predicted values on the security returns instead of...