fuzzy logic has a high potential for managing the uncertainty sources associated with the medical expert systems. application of fuzzy inference model has been widely concentrated for managing uncertainties in computer based practices of medicine. this paper has proposed two fuzzy expert systems for prognosis of the heart disease based on: 1) mamdani inference model, and 2) sugeno inference mod...

I Acknowledgments IV List of Figures X List of Tables XIV List of Abbreviations XV Publications Arising from This Work XVIII Chapter 1: Introduction .................................................................................................. 1 1.1 Aims, Significance, Novelty ........................................................................... 6 1.1.1 Aims .............................

Fuzzy Logic Systems are widely recognized to be successful at modelling uncertainty in a large variety of applications. While recently interval type-2 fuzzy logic has been credited for the ability to better deal with large amounts of uncertainty, general type2 fuzzy logic has been a steadily growing research area. All fuzzy logic systems require the accurate specification of the membership func...

TYPE-2 fuzzy sets (T2 FSs), originally introduced by Zadeh [3], provide additional design degrees of freedom in Mamdani and TSK fuzzy logic systems (FLSs), which can be very useful when such systems are used in situations where lots of uncertainties are present [4]. The implementation of this type-2 FLS involves the operations of fuzzification, inference,and output processing. We focus on ―outp...

Fuzzy Logic, introduced by Zadeh along with his introduction of fuzzy sets, is a continuous multi-valued logic system. Hence, it is a generalization of the classical logic and the classical discrete multi-valued logic (e.g. Łukasiewicz’ three/many-valued logic). Throughout the years Zadeh and other researches have introduced extensions to the theory of fuzzy setts and fuzzy logic. Notable exten...

Autonomous robot systems require complex control systems. Fuzzy Logic, a mathematical system developed by Professor Lotfi Zadeh, helps to reduce the complexity of modeling nonlinear problems. In the 1990s, Motorola developed the MC68HC12 microcontroller with native Fuzzy Logic instructions. This research determined the effectiveness of the MC68HC12’s Fuzzy Logic instructions for robotic control...