Bayesian updating of a prediction model for sewer degradation

Article Properties
Cite
Korving, H., and J. M. van Noortwijk. “Bayesian Updating of a Prediction Model for Sewer Degradation”. Urban Water Journal, vol. 5, no. 1, 2008, pp. 51-57, https://doi.org/10.1080/15730620701737157.
Korving, H., & van Noortwijk, J. M. (2008). Bayesian updating of a prediction model for sewer degradation. Urban Water Journal, 5(1), 51-57. https://doi.org/10.1080/15730620701737157
Korving H, van Noortwijk JM. Bayesian updating of a prediction model for sewer degradation. Urban Water Journal. 2008;5(1):51-7.
Journal Categories
Science
Biology (General)
Ecology
Technology
Environmental technology
Sanitary engineering
Technology
Hydraulic engineering
River, lake, and water-supply engineering (General)
Refrences
Title Journal Journal Categories Citations Publication Date
Selective inspection planning with ageing forecast for sewer types

Water Science & Technology
  • Technology: Environmental technology. Sanitary engineering
  • Technology: Engineering (General). Civil engineering (General): Environmental engineering
  • Geography. Anthropology. Recreation: Environmental sciences
  • Technology: Hydraulic engineering: River, lake, and water-supply engineering (General)
  • Technology: Environmental technology. Sanitary engineering
  • Science: Biology (General): Ecology
  • Technology: Environmental technology. Sanitary engineering
66 2002
CARE-S. Computer aided rehabilitation of sewer and storm water networks 2006
Probabilistic assessment of the performance of combined sewer systems 2004
Optimal statistical decisions 1970
10.1061/(ASCE)1076-0342(2001)7:2(77)
Citations
Title Journal Journal Categories Citations Publication Date
Analytical Inference for Inspectors’ Uncertainty Using Network-Scale Visual Inspections Journal of Computing in Civil Engineering
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Technology: Engineering (General). Civil engineering (General)
  • Technology: Engineering (General). Civil engineering (General)
  • Technology: Engineering (General). Civil engineering (General)
2023
A Two‐Stage Data‐Driven Spatiotemporal Analysis to Predict Failure Risk of Urban Sewer Systems Leveraging Machine Learning Algorithms

Risk Analysis
  • Medicine: Internal medicine: Special situations and conditions: Industrial medicine. Industrial hygiene
  • Social Sciences: Statistics
  • Science: Mathematics
  • Social Sciences: Sociology (General)
  • Social Sciences
13 2021
Combining expert knowledge and local data for improved service life modeling of water supply networks Environmental Modelling & Software
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Technology: Engineering (General). Civil engineering (General): Environmental engineering
  • Geography. Anthropology. Recreation: Environmental sciences
  • Technology: Hydraulic engineering: River, lake, and water-supply engineering (General)
  • Technology: Environmental technology. Sanitary engineering
  • Science: Biology (General): Ecology
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
27 2013
Downscale Methodology for Determining Priority Orders of the Sewer Rehabilitation

Water Environment Research
  • Technology: Engineering (General). Civil engineering (General): Environmental engineering
  • Geography. Anthropology. Recreation: Environmental sciences
  • Science: Geology
  • Technology: Hydraulic engineering: River, lake, and water-supply engineering (General)
  • Technology: Environmental technology. Sanitary engineering
  • Science: Biology (General): Ecology
  • Technology: Environmental technology. Sanitary engineering
2013
Citations Analysis
The category Science: Mathematics: Instruments and machines: Electronic computers. Computer science 2 is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Downscale Methodology for Determining Priority Orders of the Sewer Rehabilitation and was published in 2013. The most recent citation comes from a 2023 study titled Analytical Inference for Inspectors’ Uncertainty Using Network-Scale Visual Inspections. This article reached its peak citation in 2013, with 2 citations. It has been cited in 4 different journals. Among related journals, the Journal of Computing in Civil Engineering cited this research the most, with 1 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year