A genetic algorithm based fuzzy-tuned neural network

S. H. Ling; H. K. Lam; Hung Fat Frank Leung; Y. S. Lee

A genetic algorithm based fuzzy-tuned neural network

S. H. Ling
, H. K. Lam
, Hung Fat Frank Leung
, Y. S. Lee

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

6 Citations (Scopus)

Abstract

This paper presents a fuzzy-tuned neural network, which is trained by the genetic algorithm (GA). The fuzzy-tuned neural network consists of a neural-fuzzy network and a modified neural network. In the modified neural network, a novel neuron model with two activation functions is employed. The parameters of the proposed network are tuned by GA with arithmetic crossover and non-uniform mutation. Some application examples are given to illustrate the merits of the proposed network.

Original language	English
Title of host publication	IEEE International Conference on Fuzzy Systems
Pages	220-225
Number of pages	6
Publication status	Published - 14 Jul 2003
Event	The IEEE International conference on Fuzzy Systems - St. Louis, MO, United States Duration: 25 May 2003 → 28 May 2003

Conference

Conference	The IEEE International conference on Fuzzy Systems
Country/Territory	United States
City	St. Louis, MO
Period	25/05/03 → 28/05/03

Keywords

Genetic Algorithm
Neural Fuzzy Network
Neural Network

ASJC Scopus subject areas

Theoretical Computer Science
Software
Artificial Intelligence
Applied Mathematics

More information

http://hdl.handle.net/10397/1392

Cite this

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title = "A genetic algorithm based fuzzy-tuned neural network",

abstract = "This paper presents a fuzzy-tuned neural network, which is trained by the genetic algorithm (GA). The fuzzy-tuned neural network consists of a neural-fuzzy network and a modified neural network. In the modified neural network, a novel neuron model with two activation functions is employed. The parameters of the proposed network are tuned by GA with arithmetic crossover and non-uniform mutation. Some application examples are given to illustrate the merits of the proposed network.",

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Y1 - 2003/7/14

N2 - This paper presents a fuzzy-tuned neural network, which is trained by the genetic algorithm (GA). The fuzzy-tuned neural network consists of a neural-fuzzy network and a modified neural network. In the modified neural network, a novel neuron model with two activation functions is employed. The parameters of the proposed network are tuned by GA with arithmetic crossover and non-uniform mutation. Some application examples are given to illustrate the merits of the proposed network.

AB - This paper presents a fuzzy-tuned neural network, which is trained by the genetic algorithm (GA). The fuzzy-tuned neural network consists of a neural-fuzzy network and a modified neural network. In the modified neural network, a novel neuron model with two activation functions is employed. The parameters of the proposed network are tuned by GA with arithmetic crossover and non-uniform mutation. Some application examples are given to illustrate the merits of the proposed network.

KW - Genetic Algorithm

KW - Neural Fuzzy Network

KW - Neural Network

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M3 - Conference article published in proceeding or book

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BT - IEEE International Conference on Fuzzy Systems

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Y2 - 25 May 2003 through 28 May 2003

ER -

A genetic algorithm based fuzzy-tuned neural network

Abstract

Conference

Keywords

ASJC Scopus subject areas

More information

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