A dynamic hierarchical fuzzy neural network for a general continuous function

Wei Yen Wang; I. Hsun Li; Shu Chang Li; Men Shen Tsai; Shun Feng Su

doi:10.1109/FUZZY.2008.4630543

A dynamic hierarchical fuzzy neural network for a general continuous function

Wei Yen Wang, I. Hsun Li^*, Shu Chang Li, Men Shen Tsai, Shun Feng Su

^*Corresponding author for this work

Department of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

A serious problem limiting the applicability of the fuzzy neural networks is the "curse of dimensionality", especially for general continuous functions. A way to deal with this problem is to construct a dynamic hierarchical fuzzy neural network. In this paper, we propose a two-stage genetic algorithm to intelligently construct the dynamic hierarchical fuzzy neural network (HFNN) based on the merged-FNN for general continuous functions. First, we use a genetic algorithm which is popular for flowshop scheduling problems (GA_FSP) to construct the HFNN. Then, a reduced-form genetic algorithm (RGA) optimizes the HFNN constructed by GA_FSP. For a real-world application, the presented method is used to approximate the Taiwanese stock market.

Original language	English
Title of host publication	2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008
Pages	1318-1324
Number of pages	7
DOIs	https://doi.org/10.1109/FUZZY.2008.4630543
Publication status	Published - 2008
Event	2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008 - Hong Kong, China Duration: 2008 Jun 1 → 2008 Jun 6

Publication series

Name	IEEE International Conference on Fuzzy Systems
ISSN (Print)	1098-7584

Other

Other	2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008
Country/Territory	China
City	Hong Kong
Period	2008/06/01 → 2008/06/06

Keywords

Fuzzy neural networks
Genetic algorithms
Hierarchical structures

ASJC Scopus subject areas

Software
Theoretical Computer Science
Artificial Intelligence
Applied Mathematics

Access to Document

10.1109/FUZZY.2008.4630543

Cite this

Wang, WY, Li, IH, Li, SC, Tsai, MS & Su, SF 2008, A dynamic hierarchical fuzzy neural network for a general continuous function. in 2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008., 4630543, IEEE International Conference on Fuzzy Systems, pp. 1318-1324, 2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008, Hong Kong, China, 2008/06/01. https://doi.org/10.1109/FUZZY.2008.4630543

@inproceedings{9b9e976e554f4c0d97e959da9e76c7cb,

title = "A dynamic hierarchical fuzzy neural network for a general continuous function",

abstract = "A serious problem limiting the applicability of the fuzzy neural networks is the {"}curse of dimensionality{"}, especially for general continuous functions. A way to deal with this problem is to construct a dynamic hierarchical fuzzy neural network. In this paper, we propose a two-stage genetic algorithm to intelligently construct the dynamic hierarchical fuzzy neural network (HFNN) based on the merged-FNN for general continuous functions. First, we use a genetic algorithm which is popular for flowshop scheduling problems (GA_FSP) to construct the HFNN. Then, a reduced-form genetic algorithm (RGA) optimizes the HFNN constructed by GA_FSP. For a real-world application, the presented method is used to approximate the Taiwanese stock market.",

keywords = "Fuzzy neural networks, Genetic algorithms, Hierarchical structures",

author = "Wang, {Wei Yen} and Li, {I. Hsun} and Li, {Shu Chang} and Tsai, {Men Shen} and Su, {Shun Feng}",

year = "2008",

doi = "10.1109/FUZZY.2008.4630543",

language = "English",

isbn = "9781424418190",

series = "IEEE International Conference on Fuzzy Systems",

pages = "1318--1324",

booktitle = "2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008",

note = "2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008 ; Conference date: 01-06-2008 Through 06-06-2008",

}

TY - GEN

T1 - A dynamic hierarchical fuzzy neural network for a general continuous function

AU - Wang, Wei Yen

AU - Li, I. Hsun

AU - Li, Shu Chang

AU - Tsai, Men Shen

AU - Su, Shun Feng

PY - 2008

Y1 - 2008

N2 - A serious problem limiting the applicability of the fuzzy neural networks is the "curse of dimensionality", especially for general continuous functions. A way to deal with this problem is to construct a dynamic hierarchical fuzzy neural network. In this paper, we propose a two-stage genetic algorithm to intelligently construct the dynamic hierarchical fuzzy neural network (HFNN) based on the merged-FNN for general continuous functions. First, we use a genetic algorithm which is popular for flowshop scheduling problems (GA_FSP) to construct the HFNN. Then, a reduced-form genetic algorithm (RGA) optimizes the HFNN constructed by GA_FSP. For a real-world application, the presented method is used to approximate the Taiwanese stock market.

AB - A serious problem limiting the applicability of the fuzzy neural networks is the "curse of dimensionality", especially for general continuous functions. A way to deal with this problem is to construct a dynamic hierarchical fuzzy neural network. In this paper, we propose a two-stage genetic algorithm to intelligently construct the dynamic hierarchical fuzzy neural network (HFNN) based on the merged-FNN for general continuous functions. First, we use a genetic algorithm which is popular for flowshop scheduling problems (GA_FSP) to construct the HFNN. Then, a reduced-form genetic algorithm (RGA) optimizes the HFNN constructed by GA_FSP. For a real-world application, the presented method is used to approximate the Taiwanese stock market.

KW - Fuzzy neural networks

KW - Genetic algorithms

KW - Hierarchical structures

UR - http://www.scopus.com/inward/record.url?scp=55249119295&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=55249119295&partnerID=8YFLogxK

U2 - 10.1109/FUZZY.2008.4630543

DO - 10.1109/FUZZY.2008.4630543

M3 - Conference contribution

AN - SCOPUS:55249119295

SN - 9781424418190

T3 - IEEE International Conference on Fuzzy Systems

SP - 1318

EP - 1324

BT - 2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008

T2 - 2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008

Y2 - 1 June 2008 through 6 June 2008

ER -

A dynamic hierarchical fuzzy neural network for a general continuous function

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this