Abstract
Due to its natural incompleteness, a fault hypothesis generator is always considered to produce inconsistent fault hypotheses. In this paper, some notions on testing generated fault hypotheses are described. In order to discard inconsistent fault hypotheses, a technique classifying types of them and pruning them based on the types is proposed. The technique divides fault hypotheses into three types: pseudo fault hypotheses, contradicting fault hypotheses, and candidate faults. Experiments on testing fault hypotheses by pruning the pseudo and contradicting fault hypotheses have been done, and the results have shown that by doing so, inconsistent fault hypotheses can be gotten rid of considerably. Furthermore, notions to deal with candidate faults are presented as well.
| Original language | English |
|---|---|
| Title of host publication | Applications of Artificial Intelligence in Engineering |
| Publisher | Computational Mechanics Publ |
| Pages | 559-566 |
| Number of pages | 8 |
| Publication status | Published - 1994 |
| Externally published | Yes |
| Event | Proceedings of the 9th International Conference on Applications of Artificial Intelligence in Engineering - University Park, PA, USA Duration: 1994 Jul 19 → 1994 Jul 21 |
Other
| Other | Proceedings of the 9th International Conference on Applications of Artificial Intelligence in Engineering |
|---|---|
| City | University Park, PA, USA |
| Period | 94/7/19 → 94/7/21 |
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ASJC Scopus subject areas
- Software
Cite this
Issues in testing fault hypotheses. / Purna, Y. W.; Yamaguchi, Takahira.
Applications of Artificial Intelligence in Engineering. Computational Mechanics Publ, 1994. p. 559-566.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Issues in testing fault hypotheses
AU - Purna, Y. W.
AU - Yamaguchi, Takahira
PY - 1994
Y1 - 1994
N2 - Due to its natural incompleteness, a fault hypothesis generator is always considered to produce inconsistent fault hypotheses. In this paper, some notions on testing generated fault hypotheses are described. In order to discard inconsistent fault hypotheses, a technique classifying types of them and pruning them based on the types is proposed. The technique divides fault hypotheses into three types: pseudo fault hypotheses, contradicting fault hypotheses, and candidate faults. Experiments on testing fault hypotheses by pruning the pseudo and contradicting fault hypotheses have been done, and the results have shown that by doing so, inconsistent fault hypotheses can be gotten rid of considerably. Furthermore, notions to deal with candidate faults are presented as well.
AB - Due to its natural incompleteness, a fault hypothesis generator is always considered to produce inconsistent fault hypotheses. In this paper, some notions on testing generated fault hypotheses are described. In order to discard inconsistent fault hypotheses, a technique classifying types of them and pruning them based on the types is proposed. The technique divides fault hypotheses into three types: pseudo fault hypotheses, contradicting fault hypotheses, and candidate faults. Experiments on testing fault hypotheses by pruning the pseudo and contradicting fault hypotheses have been done, and the results have shown that by doing so, inconsistent fault hypotheses can be gotten rid of considerably. Furthermore, notions to deal with candidate faults are presented as well.
UR - http://www.scopus.com/inward/record.url?scp=0028590314&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0028590314&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:0028590314
SP - 559
EP - 566
BT - Applications of Artificial Intelligence in Engineering
PB - Computational Mechanics Publ
ER -