Add to ORKGThis paper reports the development of a temporal neuro-fuzzy model using fuzzy reasoning which is capable of representing the temporal information. The system is implemented as a feedforward multilayer neural network. The learning algorithm is a modification of the backpropagation algorithm. The system is aimed to be used in medical diagnosis systems
Neuro-fuzzy networks have been successfully applied to extract knowledge from data in the form of fu...
AbstractA new fuzzy reasoning that can solve two problems of conventional fuzzy reasoning by combini...
A new class of adaptive neural fuzzy networks for fuzzy modeling is introduced in this paper. It lea...
This paper introduces a new neuro-fuzzy model for constructing a knowledge base of temporal fuzzy ru...
This paper introduces a new neuro-fuzzy model for constructing a knowledge-base of temporal fuzzy ru...
The analysis and representation of temporal data are becoming increasingly important in many areas o...
In this paper, a temporal neuro-fuzzy system is presented which provides an environment that keeps t...
A neurofuzzy approach for a given set of input-output training data is proposed in two phases. First...
Knowledge acquisition is difficult, especially when the domain knowledge is not structured. In this ...
Abstract- Both fuzzy logic, as the basis of many inference systems, and Neural Networks, as a powerf...
A novel fuzzy neural network, called FuNN, is applied here for time-series modeling. FuNN models hav...
The authors of this paper analyse the input-output relation of the fuzzy system with a functional ru...
This paper briefly describes how neurofuzzy systems combine the linguistic representation of fuzzy l...
This document describes the architecture of neuro fuzzy systems. First part of the document provides...
Neuro-fuzzy networks have been successfully applied to extract knowledge from data in the form of fu...
Neuro-fuzzy networks have been successfully applied to extract knowledge from data in the form of fu...
AbstractA new fuzzy reasoning that can solve two problems of conventional fuzzy reasoning by combini...
A new class of adaptive neural fuzzy networks for fuzzy modeling is introduced in this paper. It lea...
This paper introduces a new neuro-fuzzy model for constructing a knowledge base of temporal fuzzy ru...
This paper introduces a new neuro-fuzzy model for constructing a knowledge-base of temporal fuzzy ru...
The analysis and representation of temporal data are becoming increasingly important in many areas o...
In this paper, a temporal neuro-fuzzy system is presented which provides an environment that keeps t...
A neurofuzzy approach for a given set of input-output training data is proposed in two phases. First...
Knowledge acquisition is difficult, especially when the domain knowledge is not structured. In this ...
Abstract- Both fuzzy logic, as the basis of many inference systems, and Neural Networks, as a powerf...
A novel fuzzy neural network, called FuNN, is applied here for time-series modeling. FuNN models hav...
The authors of this paper analyse the input-output relation of the fuzzy system with a functional ru...
This paper briefly describes how neurofuzzy systems combine the linguistic representation of fuzzy l...
This document describes the architecture of neuro fuzzy systems. First part of the document provides...
Neuro-fuzzy networks have been successfully applied to extract knowledge from data in the form of fu...
Neuro-fuzzy networks have been successfully applied to extract knowledge from data in the form of fu...
AbstractA new fuzzy reasoning that can solve two problems of conventional fuzzy reasoning by combini...
A new class of adaptive neural fuzzy networks for fuzzy modeling is introduced in this paper. It lea...