Structural condition assessment of sewer pipelines

Journal of Performance of Constructed Facilities

Volumn 24, Issue 2, 2010, Pages 170-179

  Khan, Zafar ^a   Zayed, Tarek ^a   Moselhi, Osama ^a  

^a Gina Cody School of Engineering and Computer Science   (Canada)

Author keywords

Assessment; Condition assessment; Neural networks; Parameters; Rehabilitation; Sensitivity analysis; Sewer mains; Sewer pipers

Indexed keywords

ARTIFICIAL NEURAL NETWORK; ASSESSMENT; BEDDING MATERIALS; CLOSED CIRCUIT TELEVISION; CONDITION ASSESSMENT; CONDITION ASSESSMENTS; DEPENDENT VARIABLES; DEVELOPED MODEL; INDEPENDENT VARIABLES; INFRASTRUCTURE NETWORKS; INPUT PARAMETER; MUNICIPAL ENGINEERS; MUNICIPAL INFRASTRUCTURE; PARAMETERS; PIPE DIAMETER; PIPE MATERIAL; PIPELINE LENGTH; PROBABILISTIC NEURAL NETWORKS; SEWER PIPELINES; SEWER PIPES; STRUCTURAL CONDITION; STRUCTURAL PERFORMANCE;

PIPE; PIPELINES; SENSITIVITY ANALYSIS; SEWERS; STEEL BRIDGES; STRUCTURAL ANALYSIS;

NEURAL NETWORKS;

EID: 77949691009     PISSN: 08873828     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)CF.1943-5509.0000081     Document Type: Conference Paper

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