Development of intelligent planning system (INPLANS): An analysis of student's performance using fuzzy systems

This paper presents an analysis of student's performance using Fuzzy Systems for a development of Intelligent Planning System (INPLANS) based on Student Performance for Academic Advisory Domain using Fuzzy Systems, Neural Networks and Genetic Algorithms. This analysis is the first step in developing INPLANS which will help the academic advisory in making plan and making the best decision for the students to get good results based on their ability. The inputs for this analysis are student's CPA and GPA. Fuzzy Inference System based on Mamdanimodel was used to process, analyse and produce student's performance. The main contribution of this system is it contributes an algorithm to analyse student's performance using Fuzzy Systems. This analysis was divided into four steps: input fuzzification, rule evaluation, aggregation of rule outputs, and defuzzification. All the steps have been tested on various students' CPA and GPA, and the experimental results have demonstrated a fast, robust, and reliable analysis simulation.