Active leakage management with bayesian networks

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dc.contributor.authorSilwimba, Felix
dc.date.accessioned2023-03-14T10:34:01Z
dc.date.available2023-03-14T10:34:01Z
dc.date.issued2021
dc.descriptionA dissertation submitted in fulfillment of the academic requirements for the degree of Master of Science in the Department of Applied Mathematics in the Faculty of Science, Agriculture and Engineering, University of Zululand, 2021.en_US
dc.description.abstractDespite the existence of different active leakage management methods and models, their implementation in most developing countries’ Water distribution systems (WDS’s) remain limited. This is attributed to some limiting challenges to leakage management faced by these WDS. Some of these include; financial constraints, poor record-keeping systems, and inadequate technicalskillsandtechnology. Thisleadsthesedistributionsystemstoadopt passive leakage management approaches that increase water losses and risk the destruction of neighboring infrastructure and water contamination. This study therefore presents a pipe leak monitoring and optimal maintenance sequencedeterminingmodellingframeworkthatisapplicableevenindistribution systems with limited data. The framework comprises of three models: a data adaptive Bayesian network(BN)modelforpredictingpipeleakprobabilitiesusedforleakagemonitoring, a water loss estimation model for estimating pipe leak water losses and a linear programming model in which water loss estimates and pipe leak predictions are used to determine the optimal pipe leak maintenance sequence. Fromtheassessmentandimplementationexampleofthemodelingframework which used simulated data, results indicate that the modeling framework is suitable for WDS with limited data.en_US
dc.identifier.urihttps://hdl.handle.net/10530/2299
dc.language.isoenen_US
dc.publisherUniversity of Zululanden_US
dc.subjectLeakage Managementen_US
dc.subjectBayesian Networksen_US
dc.titleActive leakage management with bayesian networksen_US
dc.typeThesisen_US
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