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

Abstract

The 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.