Bayesian updating of a prediction model for sewer degradation

被引：4
|
作者：
Korving, H. [1 ,2 ]
van Noortwijk, J. M. [3 ,4 ]
机构：
[1] Witteveen Bos Consulting Engineers, NL-7400 AE Deventer, Netherlands
[2] Delft Univ Technol, Fac Civil Engn & Geosci, NL-2600 GA Delft, Netherlands
[3] HKV Consultants, NL-8203 AC Lelystad, Netherlands
[4] Delft Univ Technol, Fac Elect Engn Math & Comp Sci, NL-2600 GA Delft, Netherlands
来源：
URBAN WATER JOURNAL | 2008年 / 5卷 / 01期
关键词：
asset management; Bayesian statistics; Dirichlet distribution; expert knowledge; informative prior; prediction model; sewer condition; sewer rehabilitation;
D O I：
10.1080/15730620701737157
中图分类号：
TV21 [水资源调查与水利规划];
学科分类号：
081501 ;
摘要：
Sewer degradation is mainly a stochastic process. The future condition of sewers can be predicted using models based on condition states. In The Netherlands, the SPIRIT model is being developed combining expert opinion and visual inspections. In this model the likelihood function of condition states is updated with inspections. A Dirichlet distribution is used to describe 'subjective' prior knowledge, i.e. expert knowledge. The results show that the model can be solved analytically reducing calculation time. In addition, the weight of experts and inspections is determined on the basis of prior information and data instead of estimated by subjective expert knowledge.
引用
收藏
页码：49 / 55
页数：7
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