Diagnosis system based on rough sets analysis

Junzo Watada; Shamshul Bahar Yaakob

doi:10.1109/ICGEC.2010.20

Diagnosis system based on rough sets analysis

Junzo Watada^*, Shamshul Bahar Yaakob

^*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

Nowadays, power systems play an important role in the whole electric industry. Failures of such systems should result in serious social and economical damages. Therefore, the power systems should be highly reliable. This paper presents the method to build a new type of failure diagnosis system based on rough set theory. The testing data of power systems for their failure conditions are based on experts' evaluations with uncertainty, especially little knowledge and human experiences are available on power system failure diagnosis. The rough set theory plays a vital role in handling them.

Original language	English
Title of host publication	Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010
Pages	47-50
Number of pages	4
DOIs	https://doi.org/10.1109/ICGEC.2010.20
Publication status	Published - 2010
Event	4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010 - Shenzhen Duration: 2010 Dec 13 → 2010 Dec 15

Other

Other	4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010
City	Shenzhen
Period	10/12/13 → 10/12/15

Keywords

Expert system
Failure diagnosis
Power system
Rough set

ASJC Scopus subject areas

Computational Theory and Mathematics
Theoretical Computer Science

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10.1109/ICGEC.2010.20

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title = "Diagnosis system based on rough sets analysis",

abstract = "Nowadays, power systems play an important role in the whole electric industry. Failures of such systems should result in serious social and economical damages. Therefore, the power systems should be highly reliable. This paper presents the method to build a new type of failure diagnosis system based on rough set theory. The testing data of power systems for their failure conditions are based on experts' evaluations with uncertainty, especially little knowledge and human experiences are available on power system failure diagnosis. The rough set theory plays a vital role in handling them.",

keywords = "Expert system, Failure diagnosis, Power system, Rough set",

author = "Junzo Watada and Yaakob, {Shamshul Bahar}",

year = "2010",

doi = "10.1109/ICGEC.2010.20",

language = "English",

isbn = "9780769542812",

pages = "47--50",

booktitle = "Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010",

note = "4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010 ; Conference date: 13-12-2010 Through 15-12-2010",

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T1 - Diagnosis system based on rough sets analysis

AU - Watada, Junzo

AU - Yaakob, Shamshul Bahar

PY - 2010

Y1 - 2010

N2 - Nowadays, power systems play an important role in the whole electric industry. Failures of such systems should result in serious social and economical damages. Therefore, the power systems should be highly reliable. This paper presents the method to build a new type of failure diagnosis system based on rough set theory. The testing data of power systems for their failure conditions are based on experts' evaluations with uncertainty, especially little knowledge and human experiences are available on power system failure diagnosis. The rough set theory plays a vital role in handling them.

AB - Nowadays, power systems play an important role in the whole electric industry. Failures of such systems should result in serious social and economical damages. Therefore, the power systems should be highly reliable. This paper presents the method to build a new type of failure diagnosis system based on rough set theory. The testing data of power systems for their failure conditions are based on experts' evaluations with uncertainty, especially little knowledge and human experiences are available on power system failure diagnosis. The rough set theory plays a vital role in handling them.

KW - Expert system

KW - Failure diagnosis

KW - Power system

KW - Rough set

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U2 - 10.1109/ICGEC.2010.20

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M3 - Conference contribution

AN - SCOPUS:79952540417

SN - 9780769542812

SP - 47

EP - 50

BT - Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010

T2 - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010

Y2 - 13 December 2010 through 15 December 2010

ER -

Diagnosis system based on rough sets analysis

Abstract

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Keywords

ASJC Scopus subject areas

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