Abstract: In this paper, for the first time, unsupervised neuro-fuzzy system is presented and is applied

in circuit analysis. Usually Neuro-fuzzy systems have a learning phase in which the system is trained

with input data...

Because the SVM (support vector machine) classifies data with the widest symmetric margin to decrease

the probability of the test error, modern fuzzy systems use SVM to tune the parameters of fuzzy if–then

rules. But, solving the SVM...

In this paper, the ability of fuzzy systems is used to estimate the solution of crisp

optimal control problems. To solve an optimal control problem, first the well-known Euler–

Lagrange conditions are obtained and then, the solution...

Abstract—The concepts of sets and approximate reasoning within extended fuzzy logic (FLe) provide a systematic procedure for transforming unprecisiated knowledge into a nonlinear mapping over what we define here as f-sets. ...

The author utilized neuro-fuzzy based group method of data handling (NF-GMDH) to predict the local

scour depth around pile groups under clear-water conditions. They collected the datasets from literature.

To ...

Regardless of creation method, Fuzzy rules are of great importance in the implementation and optimization systems. Although using human knowledge in creating Fuzzy rules, has the advantage of readability and is near the ...

One of the challenging concepts in mobile ad hoc networks (MANETs) is cooperation maintenance. It is important to know when and how long to do the cooperation among nodes. In this paper we introduce a new concept called ...