SELECTION OF SIMULATION VARIANCE REDUCTION TECHNIQUES THROUGH A FUZZY EXPERT SYSTEM Adrian Aderemi Adewunmi, BSc In this thesis, the design and development of a decision support system for the selection of a variance reduction technique for discrete event simulation studies is presented. In addition, the performance of variance reduction techniques as stand alone and combined application has be...

Keywords-Fuzzy reasoning, Fuzzy system, Variable weighted synthesis inference method, CRI method, Fuzzy control. 1. I N T R O D U C T I O N It is well known that fuzzy inference is a theoretical foundation of fuzzy control systems and fuzzy expert systems. At present, general fuzzy inference methods include the CRI (compositional rules of inference) method, (+,-)-centroid method, simple inferen...

Power transformers being the major apparatus in a power system, thus the assessment of transformer operating condition and lifespan have obtained crucial significance in latest years. Dissolved gas analysis (DGA) is a sensitive and reliable technique for the detection of incipient fault condition within oil-immersed transformers, which provides the basis of diagnostic evaluation of equipment he...

This paper presents an adaptive Power System Stabilizer (PSS) using an Adaptive Network Based Vague Inference System (ANVIS). An Adaptive Vague Set Based Controller Power System Stabilizer (AVCPSS) has been evaluated. This AVCPSS is capable of providing appropriate stabilization signals over a broad range of operating conditions and disturbances. A Vague Controller (VC) is synthesized by using ...

this paper demonstrates a Fuzzy Expert System that works as a very simple trading system that receives buying or selling orders from a Fuzzy Expert System. Additionally, this paper also answers two other questions posed by assignment number two of class CS657. —————————— ——————————

In this paper, we propose a novel fuzzy expert system for detection of Coronary Artery Disease, using cuckoo search algorithm. This system includes three phases: firstly, at the stage of fuzzy system design, a decision tree is used to extract if-then rules which provide the crisp rules required for Coronary Artery Disease detection. Secondly, the fuzzy system is formed by setting the intervals ...

One benefit of fuzzy systems (Zadeh, 1965; Ruspini et al., 1998; Cox, 1994) is that the rule base can be created from expert knowledge, used to specify fuzzy sets to partition all variables and a sufficient number of fuzzy rules to describe the input/output relation of the problem at hand. However, a fuzzy system that is constructed by expert knowledge alone will usually not perform as required...

This paper presents an expert system for evaluation of the unemployed at certain offered posts. The expert application uses Neuro-Fuzzy techniques for analyzing a corporate database of unemployed and enterprises profile data. The process of matching an unemployed with an offered job is performed through a Sugeno type Neuro-Fuzzy inference system. Large training sets of old historical records of...

A system combining genetic algorithms and a fuzzy-rule induction routine has been developed. Two prototype expert systems, one derived analytically, and one derived e~~pir;lcal]y by tb.e fi~q++ inrlnrtinn ..L....v..V.. system, were developed to evaluate the utility of expert system technology relative to waste nondestructive assay (NDA) data review. Technical review of waste NDA measurement dat...

In the global market place, many companies have had to adapt their strategies to meet significant challenges. A strategy adopted by some companies has been international expansion via acquisitions. The need for expert knowledge to determine an appropriate company to acquire has been complicated by the sheer size of the global market place. The costs associated with this in relation to time and ...