Students Allocation System Based on Fuzzy C-means Algorithms

Abstract

Cluster is refers to identifying the number of subclasses of c-clusters (2d” cd” n). There are two kinds of c partition of data: hard (or crisp) and soft (or fuzzy) . Two important issues are to consider how to measure the similarity between pairs of observations and how to evaluate the partitions how they are performed. Fuzzy c-means clustering is an extremely powerful classification method to accommodate fuzzy data. The application of Fuzzy set in a classification function causes the class membership to become a relative one and an project can belong to several classes at the same time but with different degree. Fuzzy c-means clustering algorithm is used in the system. It is a common practice to allocate students of certain subject into number of classes just b their ID number. In this system, allocation activity which applies the Fuzzy clustering bases on each student’s achievement. Students with similar achievement are pooled in the same class. On the other hand , students with significantly different level of achievement will be in different class. And then, it will be selected suitable lectures according to their subjects. This paper focuses on improvement of the daily learning process for students.