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 Plann...

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Main Author: Saxena, Urvashi Rahul (Author)
Format: EJournal Article
Published: Institute of Advanced Engineering and Science, 2012-12-01.
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LEADER 02189 am a22002653u 4500
001 IJERE_4429_2141
042 |a dc 
100 1 0 |a Saxena, Urvashi Rahul  |e author 
100 1 0 |e contributor 
245 0 0 |a Integrating Neuro-Fuzzy Systems to Develop Intelligent Planning Systems for Predicting Students' Performance 
260 |b Institute of Advanced Engineering and Science,   |c 2012-12-01. 
520 |a 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 
540 |a Copyright (c) 2012 Institute of Advanced Engineering and Science 
540 |a http://creativecommons.org/licenses/by-nc-nd/4.0 
546 |a eng 
690 |a Intelligent planning system (INPLANS); Neuro-fuzzy System; Grade Point Average (GPA); Cumulative Grade Point Average (CPA); Feed-Forward Architecture; Neural Networks 
655 7 |a info:eu-repo/semantics/article  |2 local 
655 7 |a info:eu-repo/semantics/publishedVersion  |2 local 
655 7 |2 local 
786 0 |n International Journal of Evaluation and Research in Education (IJERE); Vol 1, No 2: December 2012; 61-66 
786 0 |n 2620-5440 
786 0 |n 2252-8822 
786 0 |n 10.11591/ijere.v1i2 
787 0 |n https://ijere.iaescore.com/index.php/IJERE/article/view/4429/2141 
856 4 1 |u https://ijere.iaescore.com/index.php/IJERE/article/view/4429/2141  |z Get fulltext