[[abstract]]Fundamental and advanced developments in neuro-fuzzy synergisms for modeling and control are reviewed. The essential part of neuro-fuzzy synergisms comes from a common framework called adaptive networks, which unifies both neural networks and fuzzy models. The fuzzy models under the framework of adaptive networks is called adaptive-network-based fuzzy inference system (ANFIS), which possess certain advantages over neural networks. We introduce the design methods for ANFIS in both modeling and control applications. Current problems and future directions for neuro-fuzzy approaches are also addressed[[fileno]]2030226010006[[department]]資訊工程學
In this paper, the Fusion of neural and fuzzy Systems will be investigated. Membership Function Gene...
A new class of adaptive neural fuzzy networks for fuzzy modeling is introduced in this paper. It lea...
The goal of intelligent control is to achieve control objectives for complex systems where it is imp...
Adaptive Neural Fuzzy Inference Systems ANFIS have an increasing tendency to be used in scientific r...
Presenting current trends in the development and applications of intelligent systems in engineering,...
With the growing interest of using fuzzy logic in our world, adaptive fuzzy logic is keenly research...
The interest in neuro--fuzzy systems has grown tremendously over the last few years. First approache...
Integration of Artificial Neural Networks (ANN) and Fuzzy Inference Systems (FIS) have attracted the...
This document describes the architecture of neuro fuzzy systems. First part of the document provides...
This paper discusses the application of adaptive neuro-fuzzy inference system (ANFIS) control for a ...
This paper briefly describes how neurofuzzy systems combine the linguistic representation of fuzzy l...
[[abstract]]The architecture and learning procedure underlying ANFIS (adaptive-network-based fuzzy i...
To use fuzzy controllers for automization tasks appropriate fuzzy sets and fuzzy rules have to be de...
Abstract- Both fuzzy logic, as the basis of many inference systems, and Neural Networks, as a powerf...
The thesis deals with artificial neural networks theory. Subsequently, fuzzy sets are being describe...
In this paper, the Fusion of neural and fuzzy Systems will be investigated. Membership Function Gene...
A new class of adaptive neural fuzzy networks for fuzzy modeling is introduced in this paper. It lea...
The goal of intelligent control is to achieve control objectives for complex systems where it is imp...
Adaptive Neural Fuzzy Inference Systems ANFIS have an increasing tendency to be used in scientific r...
Presenting current trends in the development and applications of intelligent systems in engineering,...
With the growing interest of using fuzzy logic in our world, adaptive fuzzy logic is keenly research...
The interest in neuro--fuzzy systems has grown tremendously over the last few years. First approache...
Integration of Artificial Neural Networks (ANN) and Fuzzy Inference Systems (FIS) have attracted the...
This document describes the architecture of neuro fuzzy systems. First part of the document provides...
This paper discusses the application of adaptive neuro-fuzzy inference system (ANFIS) control for a ...
This paper briefly describes how neurofuzzy systems combine the linguistic representation of fuzzy l...
[[abstract]]The architecture and learning procedure underlying ANFIS (adaptive-network-based fuzzy i...
To use fuzzy controllers for automization tasks appropriate fuzzy sets and fuzzy rules have to be de...
Abstract- Both fuzzy logic, as the basis of many inference systems, and Neural Networks, as a powerf...
The thesis deals with artificial neural networks theory. Subsequently, fuzzy sets are being describe...
In this paper, the Fusion of neural and fuzzy Systems will be investigated. Membership Function Gene...
A new class of adaptive neural fuzzy networks for fuzzy modeling is introduced in this paper. It lea...
The goal of intelligent control is to achieve control objectives for complex systems where it is imp...