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Managing risk in civil engineering by machine learning from failures

Stone, J.R. / Blockley, D.I. / Pilsworth, B.W.

Many failures which occur in engineering can be shown to have developed though similar patterns. Machine learning using discrimination and connectivity can be used to determine these common patterns of events, and hence to build a knowledge base against which new projects may be compared. Support logic measures of uncertainty are associated with the knowledge-base concepts, and a measure of similarity is introduced.

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Managing risk in civil engineering by machine learning from failures

Stone, J.R. / Blockley, D.I. / Pilsworth, B.W.

Many failures which occur in engineering can be shown to have developed though similar patterns. Machine learning using discrimination and connectivity can be used to determine these common patterns of events, and hence to build a knowledge base against which new projects may be compared. Support logic measures of uncertainty are associated with the knowledge-base concepts, and a measure of similarity is introduced.

Managing risk in civil engineering by machine learning from failures

Stone, J.R. / Blockley, D.I. / Pilsworth, B.W.

Many failures which occur in engineering can be shown to have developed though similar patterns. Machine learning using discrimination and connectivity can be used to determine these common patterns of events, and hence to build a knowledge base against which new projects may be compared. Support logic measures of uncertainty are associated with the knowledge-base concepts, and a measure of similarity is introduced.

Zugriff

Zugriff über TIB

Verfügbarkeit in meiner Bibliothek prüfen

Bestellung bei Subito €

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Ähnliche Titel

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Titel:

Managing risk in civil engineering by machine learning from failures

Weitere Titelangaben:

Behandlung von Risiken im Bauwesen durch maschinelles Lernen von Fehlern

Beteiligte:

Stone, J.R. (Autor:in) / Blockley, D.I. (Autor:in) / Pilsworth, B.W. (Autor:in)

Erschienen in:

Proceedings. First International Symposium on Uncertainty Modeling and Analysis ; 255-259

Erscheinungsdatum:

1991

Format / Umfang:

5 Seiten, 8 Quellen

ISBN:

DOI:

https://doi.org/10.1109/ISUMA.1990.151259

Medientyp:

Aufsatz (Konferenz)

Format:

Print

Sprache:

Englisch

Schlagwörter:

FEHLERERKENNUNG , LERNENDER AUTOMAT , LERNEN , RISIKO , STOCHASTIK , MATHEMATISCHE LOGIK , EXPERTENSYSTEM , CONNECTIVITY , WISSENSBANK , RISK MANAGEMENT

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