Sewer Condition Prediction and Analysis of Explanatory Factors

Sewer Condition Prediction and Analysis of Explanatory Factors

Sewer condition is commonly assessed using closed-circuit television (CCTV) inspections. In this paper, we combine inspection results, pipe attributes, network data, and data on pipe environment to predict pipe condition and to discover which factors affect it. We apply the random forest algorithm t...

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Bibliographic Details
Main Authors: Tuija Laakso, Teemu Kokkonen, Ilkka Mellin, Riku Vahala
Format: Article
Language:English
Published: MDPI AG 2018-09-01
Series:Water
Subjects:
Boruta algorithm
logistic regression
partial dependence plot
random forest
sewer condition
variable selection
Online Access:http://www.mdpi.com/2073-4441/10/9/1239

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