Reliability Modelling and Analysis of Water Distribution Network Based on Backpropagation Recursive Processes with Real Field Data

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F20%3A43916403" target="_blank" >RIV/62156489:43110/20:43916403 - isvavai.cz</a>

Alternative codes found

RIV/60162694:G43__/20:00537164

Result on the web

<a href="https://doi.org/10.1016/j.measurement.2019.107026" target="_blank" >https://doi.org/10.1016/j.measurement.2019.107026</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.measurement.2019.107026" target="_blank" >10.1016/j.measurement.2019.107026</a>

Result language

angličtina

Original language name

Reliability Modelling and Analysis of Water Distribution Network Based on Backpropagation Recursive Processes with Real Field Data

Original language description

Any water distribution network (WDN) is a key element in critical infrastructure. As time series data mining and modelling are developing apace, these provide promising tools for the research of water resources management. The aim of this article is to explain how incomplete information on the failures in water mains can be used and processed effectively. The data available and under investigation are the truncated failure field data of a regional water distribution network recorded during the last 15 years. We introduce the application of novel, non-trivial dynamic backpropagation recursive time-series models which are later successfully validated by the recorded data. Real field data of a WDN were used while these data were elaborated with a backpropagation Kalman recursor. The results can be used for predicting the reliability of a WDN, or as inputs into a water management system to optimise maintenance, crisis management and emergency planning.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10103 - Statistics and probability

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Measurement

ISSN

0263-2241

e-ISSN

—

Volume of the periodical

149

Issue of the periodical within the volume

January

Country of publishing house

GB - UNITED KINGDOM

Number of pages

14

Pages from-to

"UNSP 107026"

UT code for WoS article

000490131400047

EID of the result in the Scopus database

2-s2.0-85072192105