Sewer deterioration modeling with condition data lacking historical records

Water Research

Volumn 47, Issue 17, 2013, Pages 6762-6779

  Egger, C ^a,b   Scheidegger, A ^a   Reichert, P ^a,b   Maurer, M ^a,b  

^a SWISS FEDERAL INSTITUTE OF AQUATIC SCIENCE AND TECHNOLOGY   (Switzerland)

^b ETH ZURICH   (Switzerland)

Author keywords

Bayesian inference; Data management; Deterioration model; Likelihood; Rehabilitation model; Survival selection bias

Indexed keywords

BAYESIAN NETWORKS; CALIBRATION; IMPORTANCE SAMPLING; INFERENCE ENGINES; INFORMATION MANAGEMENT; SENSITIVITY ANALYSIS; SEWERS; UNCERTAINTY ANALYSIS;

BAYESIAN INFERENCE; DETERIORATION MODELING; EFFICIENT IMPLEMENTATION; HISTORICAL INFORMATION; LIKELIHOOD; REHABILITATION PLANNING; SELECTION BIAS; SEWER REHABILITATION;

DETERIORATION;

BAYESIAN ANALYSIS; CALIBRATION; DATA MANAGEMENT; DATA SET; HISTORICAL RECORD; NUMERICAL MODEL; PARAMETERIZATION; PIPE; PREDICTION; REFURBISHMENT; SENSITIVITY ANALYSIS; SEWER NETWORK;

ARTICLE; BAYES THEOREM; CALIBRATION; CONCEPTUAL FRAMEWORK; LIFESPAN; MATHEMATICAL MODEL; PRIORITY JOURNAL; PROBABILITY; QUALITY CONTROL; SAMPLING; SENSITIVITY ANALYSIS; SEWER; UNCERTAINTY; WATER MANAGEMENT; WATER SUPPLY;

BAYESIAN INFERENCE; DATA MANAGEMENT; DETERIORATION MODEL; LIKELIHOOD; REHABILITATION MODEL; SURVIVAL SELECTION BIAS;

CALIBRATION; LIKELIHOOD FUNCTIONS; MARKOV CHAINS; MODELS, THEORETICAL; MONTE CARLO METHOD; SANITARY ENGINEERING; SEWAGE;

EID: 84886101573     PISSN: 00431354     EISSN: 18792448     Source Type: Journal    
DOI: 10.1016/j.watres.2013.09.010     Document Type: Article

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