Design of Fuzzy Membership Functions for Predicting Student’s Knowledge Performance

Abstract

A Fuzzy logic controller is a problem-solving control system that provides means for representing approximate knowledge. The output of a fuzzy controller is derived from the fuzzifications of crisp (numerical) inputs using associated membership functions. The crisp inputs are usually converted to the different members of the associated linguistic variables based on their respective values. This point is evident enough to show that the output of a fuzzy logic controller is heavily dependent on its memberships of the different membership functions, which can be considered as a range of inputs [4]. Input membership functions can take various forms trapezoids, triangles, bell curves, singleton or any other shape that accurately enables the distribution of information within the system, in as much as the shape provides a region of transition between adjacent membership functions.