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Journal ArticleDOI

Radial basis function based adaptive fuzzy systems and their applications to system identification and prediction

Kwang Bo Cho, +1 more
- 11 Nov 1996 - 
- Vol. 83, Iss: 3, pp 325-339
TLDR
A neuro-fuzzy system with adaptive capability to extract fuzzy If Then rules from input and output sample data through learning is described and its validity and effectiveness are demonstrated using the RBF based AFS.
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This article is published in Fuzzy Sets and Systems.The article was published on 1996-11-11. It has received 318 citations till now. The article focuses on the topics: Adaptive neuro fuzzy inference system & Fuzzy classification.

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Citations
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Journal ArticleDOI

Neuro-fuzzy rule generation: survey in soft computing framework

TL;DR: This article proposes to bring the various neuro-fuzzy models used for rule generation under a unified soft computing framework, and includes both rule extraction and rule refinement in the broader perspective of rule generation.
Journal ArticleDOI

Designing fuzzy inference systems from data: An interpretability-oriented review

TL;DR: The paper analyzes the main methods for automatic rule generation and structure optimization and grouped them into several families and compared according to the rule interpretability criterion.
Journal ArticleDOI

Dynamic fuzzy neural networks-a novel approach to function approximation

TL;DR: Simulation studies and comprehensive comparisons with some other learning algorithms demonstrate that a more compact structure with higher performance can be achieved by the proposed approach.
Journal ArticleDOI

A fast approach for automatic generation of fuzzy rules by generalized dynamic fuzzy neural networks

TL;DR: Comprehensive comparisons with other latest approaches show that the proposed approach is superior in terms of learning efficiency and performance.
Journal ArticleDOI

Sequential Adaptive Fuzzy Inference System (SAFIS) for nonlinear system identification and prediction

TL;DR: In SAFIS, the concept of ''Influence'' of a fuzzy rule is introduced and using this the fuzzy rules are added or removed based on the input data received so far.
References
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Journal ArticleDOI

Fuzzy identification of systems and its applications to modeling and control

TL;DR: A mathematical tool to build a fuzzy model of a system where fuzzy implications and reasoning are used is presented and two applications of the method to industrial processes are discussed: a water cleaning process and a converter in a steel-making process.
Journal ArticleDOI

Multilayer feedforward networks are universal approximators

TL;DR: It is rigorously established that standard multilayer feedforward networks with as few as one hidden layer using arbitrary squashing functions are capable of approximating any Borel measurable function from one finite dimensional space to another to any desired degree of accuracy, provided sufficiently many hidden units are available.
Book

Pattern classification and scene analysis

TL;DR: In this article, a unified, comprehensive and up-to-date treatment of both statistical and descriptive methods for pattern recognition is provided, including Bayesian decision theory, supervised and unsupervised learning, nonparametric techniques, discriminant analysis, clustering, preprosessing of pictorial data, spatial filtering, shape description techniques, perspective transformations, projective invariants, linguistic procedures, and artificial intelligence techniques for scene analysis.
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