Integrating Neuro-Fuzzy Systems to Develop Intelligent Planning Systems for Predicting Students’ Performance

This paper presents a simulation of Neuro-Fuzzy application for analyzing students’ performance based on their CPA and GPA. This analysis is an attempt for extension of Analysis on Student’s Performance Using Fuzzy Systems. This paper focuses to support the development of Intelligent Planning System (INPLANS) using Fuzzy Systems, Neural Networks, and Genetic Algorithms which will be used by the Academic Advisory Domain in educational institutions by evaluating and predicting students’ performance as well as comparing the results with the previous study. The Neuro-Fuzzy model is feed-forward architecture with five layers of neurons and four connections. System evaluation has been done for about 20- 26 cases of students’ results. The results depict that there has been a significant improvement in the performance of students’ as compared to the prediction of the same case using Fuzzy Systems.