Abstract—Most methods of fuzzy rule-based system identifica-tion (SI) either ignore feature analysis or do it in a separate phase. This paper proposes a novel neuro-fuzzy system that can simulta-neously do feature analysis and SI in an integrated manner. It is a five-layered feed-forward network for realizing a fuzzy rule-based system. The second layer of the net is the most important one, which along with fuzzification of the input also learns a modu-lator function for each input feature. This enables online selection of important features by the network. The system is so designed that learning maintains the nonnegative characteristic of certainty factors of rules. The proposed network is tested on both synthetic and real data sets and the...
Abstruct-Fuzzy rule-base modeling is the task of identifying the structure and the parameters of a f...
AbstractMultilayer neural networks with error back-propagation learning algorithms have the capabili...
In this paper, the Fusion of neural and fuzzy Systems will be investigated. Membership Function Gene...
Abstract—Most methods of classification either ignore feature analysis or do it in a separate phase,...
AbstractMultilayer neural networks with error back-propagation learning algorithms have the capabili...
This paper proposes a neural network for building and optimizing fuzzy models. The network can be re...
This paper proposes an integrated approach to rule structure and parameter identification for fuzzy ...
In previous papers, we presented an empirical methodology based on Neural Networks for obtaining fu...
[[abstract]]It has been known that fuzzy system provide a framework to handle uncertainties and vagu...
Abstract- Both fuzzy logic, as the basis of many inference systems, and Neural Networks, as a powerf...
This paper proposes a hybrid architecture based on neural networks, fuzzy systems, and n-uninorms fo...
In this paper we propose an approach to fuzzy rule extraction, which casts into the so-called Knowle...
This document describes the architecture of neuro fuzzy systems. First part of the document provides...
A Fuzzy logic system has been shown to be able to arbitrarily approximate any nonlinear function and...
This paper discusses the question how the membership functions in a fuzzy rule based system can be e...
Abstruct-Fuzzy rule-base modeling is the task of identifying the structure and the parameters of a f...
AbstractMultilayer neural networks with error back-propagation learning algorithms have the capabili...
In this paper, the Fusion of neural and fuzzy Systems will be investigated. Membership Function Gene...
Abstract—Most methods of classification either ignore feature analysis or do it in a separate phase,...
AbstractMultilayer neural networks with error back-propagation learning algorithms have the capabili...
This paper proposes a neural network for building and optimizing fuzzy models. The network can be re...
This paper proposes an integrated approach to rule structure and parameter identification for fuzzy ...
In previous papers, we presented an empirical methodology based on Neural Networks for obtaining fu...
[[abstract]]It has been known that fuzzy system provide a framework to handle uncertainties and vagu...
Abstract- Both fuzzy logic, as the basis of many inference systems, and Neural Networks, as a powerf...
This paper proposes a hybrid architecture based on neural networks, fuzzy systems, and n-uninorms fo...
In this paper we propose an approach to fuzzy rule extraction, which casts into the so-called Knowle...
This document describes the architecture of neuro fuzzy systems. First part of the document provides...
A Fuzzy logic system has been shown to be able to arbitrarily approximate any nonlinear function and...
This paper discusses the question how the membership functions in a fuzzy rule based system can be e...
Abstruct-Fuzzy rule-base modeling is the task of identifying the structure and the parameters of a f...
AbstractMultilayer neural networks with error back-propagation learning algorithms have the capabili...
In this paper, the Fusion of neural and fuzzy Systems will be investigated. Membership Function Gene...