In spite of its successes as a tool in the field of engineering, fuzzy set theory has yet to achieve the universal footing that probability theory has across the various fields of mathematics, technology, philosophy and psychology. This paper sets out points of critique brought up regarding the fuzzy approach and seeks to analyze them, focusing on the question of whether anything that can be do...

This paper deals with using fuzzy logic to minimize uncertainty effects in surveillance. It studies the conception of an efficient fuzzy expert system that had two characteristics: generic and robust to uncertainties. Analyzing distance between variables optimal and real values is the main idea of the research. Fuzzy inference system decides, then, about significant variables state: normal or a...

Fuzzy measure, as a non-additive metric, is an effective tool for information fusion. Constructing a determining mechanism for fuzzy measure with operability is the key focus in academic and application fields. In this paper, we first take core samples as knowledge carriers on the decision information system. According to changes of knowledge carriers, we second give a knowledge-based metric of...

This paper presents a supervised training algorithm that implements fuzzy reasoning on a spiking neural network. Neuron selectivity is facilitated using receptive fields that enable individual neurons to be responsive to certain spike train frequencies. The receptive fields behave in a similar manner as fuzzy membership functions. The network is supervised but learning only occurs locally as in...

The techniques in artificial intelligence are used in almost all the fields where human reasoning and uncertainties can be effectively modeled. The popular techniques in AI are fuzzy logic and neural networks which can be used either separately or applied together. When they are used in combined way, they are called Neuro-Fuzzy Systems. The reasons to combine these two paradigms come out of the...

The study of theory of fuzzy sets was initiated by Zadeh in 1965. Since then many authors have extended and developed the theory of fuzzy sets in the fields of topology and analysis. The notion of fuzzy metric spaces has very important applications in quantum particle physics. As a result many authors have extended the Banach's Contraction Principle to fuzzy metric spaces and proved fixed ...

Zadeh in 1965 introduce the concept of a fuzzy set which now have a wide range of applications in various fields of Engineering Sciences, Computer Science and Management Sciences. It is worth mentioning here that for applications of fuzzy sets mostly associative algebraic structures are used such as in 2003, Mordeson, Malik and Kuroki have discovered the applications of fuzzy semigroups in fuzz...

The one-dimensional N ×N -matrix Chern-Simons action is given, for large N and for slowly varying fields, by the (2k + 1)-dimensional Chern-Simons action SCS , where the gauge fields in SCS parametrize the different ways in which the large N limit can be taken. Since some of these gauge fields correspond to the isometries of the space, we argue that gravity on fuzzy spaces can be described by t...

The Fuzzy set theory has been applied in many fields such as management, engineering and almost in every business enterprise as well as day to day activities. Ordering fuzzy numbers plays an important role in approximate reasoning, optimization, forecasting, decision making, risk analysis, controlling, scheduling and various other usages in our day to day activities. This paper describes a rank...