BAYESIAN BELIEF NETWORK AND FUZZY LOGIC ADAPTIVE MODELING OF DYNAMIC SYSTEM: EXTENSION AND COMPARISON

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dc.contributor.advisorMODARRES, MOHAMMADen_US
dc.contributor.authorCHENG, PING DANNYen_US
dc.contributor.departmentReliability Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2010-10-07T05:54:00Z
dc.date.available2010-10-07T05:54:00Z
dc.date.issued2010en_US
dc.description.abstractThe purpose of this thesis is to develop, expand, compare and contrast two methodologies, namely BBN and FLM, which are used in the modeling of the dynamics of physical system behavior and are instrumental in a better understanding on the POF. The paper begins with an introduction of the proposed approaches in the modeling of complex physical systems, followed by a quick literature review of FLM and BBN. This thesis uses an existing pump system [3] as a case study, where the resulting NPSHA data obtained from the applications of BBN and FLM are compared with the outputs derived from the implementation of a Mathematical Model. Based on these findings, discussions and analyses are made, including the identification of the respective strengths and weaknesses posed by the two methodologies. Last but not least, further extensions and improvements towards this research are discussed at the end of this paper.en_US
dc.identifier.urihttp://hdl.handle.net/1903/10870
dc.subject.pqcontrolledEngineering, Mechanicalen_US
dc.subject.pqcontrolledEngineering, Generalen_US
dc.subject.pquncontrolledBayesian Belief Networken_US
dc.subject.pquncontrolledComplex Dynamic Systemen_US
dc.subject.pquncontrolledComplex Physical Systemen_US
dc.subject.pquncontrolledFuzzy Logic Modelingen_US
dc.subject.pquncontrolledMathematical Modelen_US
dc.titleBAYESIAN BELIEF NETWORK AND FUZZY LOGIC ADAPTIVE MODELING OF DYNAMIC SYSTEM: EXTENSION AND COMPARISONen_US
dc.typeThesisen_US

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