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Doctoral Thesis / Dissertation from the year 2010 in the subject Engineering - Artificial Intelligence, grade: PhD, Korea University, Seoul (College of Engineering - Dept of Industrial Systems and Information Engineering), course: Intelligence Control and Artificial Intelligence, language: English, abstract: Fuzzy Logic (FL) is a particular area of interest in the study of Artificial intelligence(AI) based on the idea that in fuzzy sets each element in the set can assume a value from0 to 1, not just 0 or 1, as in classic or crisp set theory. The gradation in the extent towhich an element is belonging to the relevant sets is called the degree of membership.This degree of membership is a measure of the element's belonging to the set, and thus ofthe precision with which it explains the phenomenon being evaluated. A linguisticexpression is given to each fuzzy set. The information contents of the fuzzy rules are thenused to infer the output using a suitable inference engine. The key contribution of fuzzylogic in computation of information described in natural language made it applicable to avariety of applications and problem domains; from simple control systems to humandecision support systems. Yet, despite its long-standing origins, it is a relatively new field,and as such leaves much room for development.The thesis presents two novel applications of fuzzy systems; a human decisionsupport system to help teachers to fairly evaluate students and two hybrid intelligentfuzzy sys...
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