A step by step methodology for learning fuzzy rules is presented. This methodology tries to be general enough to give a framework within which diierent learning methods in an environment of uncertainty and imprecision could be developed. The nal product will always be an uncertainty distribution on the diierent rules representing the behaviour of the system. The particular uncertainty distribut...

in most of the real-life applications we deal with the problem of transporting some special fruits, as banana, which has particular production and distribution processes. in this paper we restrict our attention to formulating and solving a new bi-criterion problem on a network in which in addition to minimizing the traversing costs, admissibility of the quality level of fruits is a main objecti...

The extension principle defines the arithmetic operations on fuzzy numbers. In the extension principle one can use any t-norm for modeling the conjunction operator. It is therefore important to know, which t-norms are consistent with a particular type of fuzzy number. We call a t-norm consistent, if the arithmetic operation is closed. In this paper we investigate the addition of sigmoid and two...

In this work we consider a very general principle for fuzzy rule interpolation methods based on an interpretation of the generalized modus ponens rule in terms of closeness relations. Then we present two particular instances of the general principle when the closeness relations are defined from parametric families of similarity fuzzy relations on the input and output spaces. The case of multipl...

Prostate Cancer Foundation of Australia (PCFA) launched its Rural Education Roadshow program in 2013. Funded through the Commonwealth Government, and modelled on the Western Australia Cancer & Palliative Care Network framework, the program brought a structured prostate cancer education program to regional, rural and remote communities across Australia. The Roadshow aimed to: • improve local kno...

In order to apply the concept of boundedness, so crucial in the theory of metric spaces, to the case of a general topological space Hu Sze-Tsen introduced the notions of a bornological space and of boundedness for a mapping of bornological spaces. In this work we discuss two alternative approaches how the concepts of bornology and boundedness can be extended to the case of fuzzy sets and many-v...

This paper is devoted to the modeling and dSPACE implementation of three-phase squirrel-cage induction motor control using the constant Volts per Hertz principle and rotor flux oriented control (RFOC) strategy. A fuzzy PI controller is used in the speed control loop. Experimental results are compared for two different controls using a dSPACE system with DS1104 controller board based on digital ...

In this paper, a micromilling type-2 fuzzy tool condition monitoring system based on multiple AE acoustic emission signal features is proposed. The type-2 fuzzy logic system is used as not only a powerful tool to model acoustic emission signal, but also a great estimator for the ambiguities and uncertainties associated with the signal itself. Using the results of root-mean-square error estimati...

In a virtual prototyping context the importance of physical uncertainty modelling has become more evident. The increased computational performance over the last years enlarges the potential in the use of large models (more DOF’s) and in the application of more advanced numerical methods. This results in more accurate models from the numerical point of view. Realistic numerical modelling however...

Methods for analyzing or learning from “fuzzy data” have attracted increasing attention in recent years. In many cases, however, existing methods (for precise, non-fuzzy data) are extended to the fuzzy case in an ad-hoc manner, and without carefully considering the interpretation of a fuzzy set when being used for modeling data. Distinguishing between an ontic and an epistemic interpretation of...