The purpose of this paper is to provide a review of the current state of fuzzy logic theory in epidemiology, which is a recent area of research. We present four applications of fuzzy logic theory in epidemic problems, using linguistic fuzzy models, possibility measure, probability of fuzzy events and fuzzy decision making techniques. The results demonstrate that the applications of fuzzy sets i...

This article is a short position paper in which the author outlines his (necessarily subjective) perception of current research in fuzzy machine learning, that is, the use of formal concepts and mathematical tools from fuzzy sets and fuzzy logic in the field of machine learning. The paper starts with a critical appraisal of previous contributions to fuzzy machine learning and ends with a sugges...

When I started interacting with logicians, I was surprised to learn that fuzzy logic is still a big and active field of basic research. This surprise stemmed from my experience with fuzzy logic in my own field, linguistic semantics: In semantics, fuzzy logic was explored in the analysis of vagueness in the early seventies by Lakoff [10], but has been regarded as unsuitable for the analysis of l...

The fifteen responses to my paper provide an exceptionally wide range of perspectives on the current state of research on fuzzy logic and its applications. Overall, I find that with most commentators I agree more than I disagree. In this response, I shall try to steer a middle course between simply repeating points of agreement and narrowly countering points of disagreement. My comments are div...

Fuzzy Analogy of Linear Systems Abstract: In this start up study fuzzy logic theory is incorporated into modelling of linear systems whose parameters and variables subject to uncertainty. The major intention is to try to understand the complicated mathematical background and therefore the principles and formulations can be properly interpreted into transparent engineering implementation. Two ex...

the idea of this paper is designing an automatic fault detection system based on fuzzy logic, therefore two signals of pmsm in fault condition are analyzed for inter turn fault detection: current and torque. in this fault type there is some distortion in these signals, but it is not good enough to detecting with fuzzy logic solely, so with combination of wavelet transform and fcm a new method f...

This note points out a terminological clash between Atanassov's “intuitionistic fuzzy sets” and what is currently understood as intuitionistic logic. They differ both by their motivations and their underlying mathematical structure. Furthermore, Atanassov's construct is isomorphic to interval-valued fuzzy sets and other similar notions, even if their interpretive settings and motivation are qui...

Among other applications, multi-adjoint lattices have been successfully used for modeling flexible notions of truth-degrees in the fuzzy extension of logic programming called MALP (Multi-Adjoint Logic Programming). In this paper we focus in the completion of such mathematical construct by adapting the classical notion of Dedekind-MacNeille in order to relax this usual hypothesis on such kind of...

The proposed fuzzy adaptive PI control algorithm is designed for non-linear level process to improve the control performance better than the conventional PI controller. The conventional PI controller works well only if the mathematical model of the system could be computed. Hence it is difficult to implement the conventional PI controller for variable as well as complicated systems. But fuzzy l...

We consider a generalized model of neural network with a fuzziness and chaos. The origin of the fuzzy signals lies in complex biochemical and electrical processes of the synapse and dendrite membrane excitation and the inhibition mechanism. The mathematical operations included into fuzzy neural network modeling are: the scalar product between inputs of layers and synaptic weights is replaced by...