Study on relationships between climate-related covariates and pipe bursts using evolutionary-based modelling
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @Article{Laucelli:2014:JoH,
-
author = "Daniele Laucelli and Balvant Rajani and
Yehuda Kleiner and Orazio Giustolisi",
-
title = "Study on relationships between climate-related
covariates and pipe bursts using evolutionary-based
modelling",
-
journal = "Journal of Hydroinformatics",
-
year = "2014",
-
volume = "16",
-
number = "4",
-
pages = "743--757",
-
month = "1 " # jul,
-
keywords = "genetic algorithms, genetic programming, data-mining,
Evolutionary Polynomial Regression, impact of climate
on water main bursts, knowledge discovery, pipe burst
modelling",
-
URL = "https://iwaponline.com/jh/article-pdf/16/4/743/387365/743.pdf",
-
DOI = "doi:10.2166/hydro.2013.082",
-
abstract = "Researchers extensively studied external loads since
they are widely recognized as significant contributors
to water pipe failures. Physical phenomena that affect
pipe bursts, such as pipe-environment interactions, are
very complex and only partially understood. This paper
analyses the possible link between pipe bursts and
climate-related factors. Many water utilities observed
consistent occurrence of peaks in pipe bursts in some
periods of the year, during winter or summer. The paper
investigates the relationships between climate data
(i.e., temperature and precipitation-related
covariates) and pipe bursts recorded during a 24-year
period in Scarborough (Ontario, Canada). The
Evolutionary Polynomial Regression modelling paradigm
is used here. This approach is broader than statistical
modelling, implementing a multi-modelling approach,
where a multi-objective genetic algorithm is used to
get optimal models in terms of parsimony of
mathematical expressions vs. fitting to data. The
analyses yielded interesting results, in particular for
cold seasons, where the discerned models show good
accuracy and the most influential explanatory variables
are clearly identified. The models discerned for warm
seasons show lower accuracy, possibly implying that the
overall phenomena that underlay the generation of pipe
bursts during warm seasons cannot be thoroughly
explained by the available climate-related
covariates.",
-
notes = "This content is only available as a PDF.",
- }
Genetic Programming entries for
Daniele B Laucelli
Balvant Rajani
Yehuda Kleiner
Orazio Giustolisi
Citations