Gain estimation for an AC power line data network transmitter using a neural-fuzzy network and an improved genetic algorithm

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

Gain estimation for an AC power line data network transmitter using a neural-fuzzy network and an improved genetic algorithm

H. K. Lam, S. H. Ling, Hung Fat Frank Leung, P. K.S. Tam, 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

Abstract

This paper presents the estimation of the transmission gain for an AC power line data network in an intelligent home. The estimated gain ensures the transmission reliability and efficiency. A neural-fuzzy network with rule switches is proposed to perform the estimation. An improved genetic algorithm is proposed to tune the parameters and the rules of the proposed neural-fuzzy network. By turning on or off the rule switches, an optimal rule base can be obtained. An application example will be given.

Original language	English
Title of host publication	IEEE International Conference on Fuzzy Systems
Pages	167-172
Number of pages	6
Publication status	Published - 11 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

ASJC Scopus subject areas

Theoretical Computer Science
Software
Artificial Intelligence
Applied Mathematics

More information

http://hdl.handle.net/10397/1391

Cite this

@inproceedings{1065fa3b72cf416ab33c9fef72b8f559,

title = "Gain estimation for an AC power line data network transmitter using a neural-fuzzy network and an improved genetic algorithm",

abstract = "This paper presents the estimation of the transmission gain for an AC power line data network in an intelligent home. The estimated gain ensures the transmission reliability and efficiency. A neural-fuzzy network with rule switches is proposed to perform the estimation. An improved genetic algorithm is proposed to tune the parameters and the rules of the proposed neural-fuzzy network. By turning on or off the rule switches, an optimal rule base can be obtained. An application example will be given.",

author = "Lam, {H. K.} and Ling, {S. H.} and Leung, {Hung Fat Frank} and Tam, {P. K.S.} and Lee, {Y. S.}",

year = "2003",

month = jul,

day = "11",

language = "English",

pages = "167--172",

booktitle = "IEEE International Conference on Fuzzy Systems",

note = "The IEEE International conference on Fuzzy Systems ; Conference date: 25-05-2003 Through 28-05-2003",

}

Lam, HK, Ling, SH, Leung, HFF, Tam, PKS & Lee, YS 2003, Gain estimation for an AC power line data network transmitter using a neural-fuzzy network and an improved genetic algorithm. in IEEE International Conference on Fuzzy Systems. pp. 167-172, The IEEE International conference on Fuzzy Systems, St. Louis, MO, United States, 25/05/03. <http://hdl.handle.net/10397/1391>

Gain estimation for an AC power line data network transmitter using a neural-fuzzy network and an improved genetic algorithm. / Lam, H. K.; Ling, S. H.; Leung, Hung Fat Frank et al.
IEEE International Conference on Fuzzy Systems. 2003. p. 167-172.

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

TY - GEN

T1 - Gain estimation for an AC power line data network transmitter using a neural-fuzzy network and an improved genetic algorithm

AU - Lam, H. K.

AU - Ling, S. H.

AU - Leung, Hung Fat Frank

AU - Tam, P. K.S.

AU - Lee, Y. S.

PY - 2003/7/11

Y1 - 2003/7/11

N2 - This paper presents the estimation of the transmission gain for an AC power line data network in an intelligent home. The estimated gain ensures the transmission reliability and efficiency. A neural-fuzzy network with rule switches is proposed to perform the estimation. An improved genetic algorithm is proposed to tune the parameters and the rules of the proposed neural-fuzzy network. By turning on or off the rule switches, an optimal rule base can be obtained. An application example will be given.

AB - This paper presents the estimation of the transmission gain for an AC power line data network in an intelligent home. The estimated gain ensures the transmission reliability and efficiency. A neural-fuzzy network with rule switches is proposed to perform the estimation. An improved genetic algorithm is proposed to tune the parameters and the rules of the proposed neural-fuzzy network. By turning on or off the rule switches, an optimal rule base can be obtained. An application example will be given.

UR - http://www.scopus.com/inward/record.url?scp=0038199535&partnerID=8YFLogxK

M3 - Conference article published in proceeding or book

SP - 167

EP - 172

BT - IEEE International Conference on Fuzzy Systems

T2 - The IEEE International conference on Fuzzy Systems

Y2 - 25 May 2003 through 28 May 2003

ER -

Gain estimation for an AC power line data network transmitter using a neural-fuzzy network and an improved genetic algorithm

Abstract

Conference

ASJC Scopus subject areas

More information

Other files and links

Fingerprint

Cite this