Integrating Neuro-Fuzzy Systems to Develop Intelligent Planning Systems for Predicting Students’ Performance
Urvashi Rahul Saxena
Abstract
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.
DOI: http://dx.doi.org/10.11591/ijere.v1i2.738
Keywords
Intelligent planning system (INPLANS); Neuro-fuzzy System; Grade Point Average (GPA); Cumulative Grade Point Average (CPA); Feed-Forward Architecture; Neural Networks
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Copyright (c) 2012 Institute of Advanced Engineering and Science
International Journal of Evaluation and Research in Education (IJERE) Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU)
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