Applications of machine learning in pipeline monitoring

Congress on Computing in Civil Engineering, Proceedings

Volumn , Issue , 2011, Pages 242-249

  Ying, Yujie ^a   Harley, Joel ^a   Garrett Jr , James H ^a   Jin, Yuanwei ^b   Oppenheim, Irving J ^a   Shi, Jun ^a   Soibelman, Lucio ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

^b UNIVERSITY OF MARYLAND EASTERN SHORE   (United States)

Author keywords

Gas pipelines; Monitoring; Technology

Indexed keywords

AIR PRESSURES; CLASSIFICATION ALGORITHM; COMBINED METHOD; CORRELATION COEFFICIENT; DAMAGE DETECTION SYSTEMS; DATA SETS; DETECTION METHODS; MACHINE LEARNING TECHNIQUES; PEAK AMPLITUDE; PIPELINE MONITORING; SHIFT INVARIANT; TRAINING AND TESTING;

ADAPTIVE BOOSTING; ATMOSPHERIC PRESSURE; CIVIL ENGINEERING; CLASSIFICATION (OF INFORMATION); FEATURE EXTRACTION; GAS PIPELINES; LEARNING SYSTEMS; MONITORING; SIGNAL DETECTION; STRUCTURAL HEALTH MONITORING; TECHNOLOGY;

DAMAGE DETECTION;

EID: 80053143978     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1061/41182(416)30     Document Type: Conference Paper

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