Students Classification With Adaptive Neuro Fuzzy

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Author(s)

Mohammad Saber Iraji 1,* Majid Aboutalebi 2 Naghi. R. Seyedaghaee 3 Azam Tosinia 3

1. Department of Computer science, Young Researchers Club sari Branch, Islamic Azad University, sari, Iran

2. Department of Computer Engineering , Islamic Azad University, Sari Branch, Sari, Iran

3. Department of Computer Engineering, Aliabad Katoul Branch, Islamic Azad University,Aliabad Katoul, Iran

* Corresponding author.

DOI: https://doi.org/10.5815/ijmecs.2012.07.06

Received: 20 Mar. 2012 / Revised: 7 May 2012 / Accepted: 3 Jun. 2012 / Published: 8 Jul. 2012

Index Terms

Adaptive neuro fuzzy, Neural network, Students classification, Lvq

Abstract

Identifying exceptional students for scholarships is an essential part of the admissions process in undergraduate and postgraduate institutions, and identifying weak students who are likely to fail is also important for allocating limited tutoring resources. In this article, we have tried to design an intelligent system which can separate and classify student according to learning factor and performance. a system is proposed through Lvq networks methods, anfis method to separate these student on learning factor . In our proposed system, adaptive fuzzy neural network(anfis) has less error and can be used as an effective alternative system for classifying students.

Cite This Paper

Mohammad Saber Iraji, Majid Aboutalebi, Naghi. R. Seyedaghaee, Azam Tosinia, "Students Classification With Adaptive Neuro Fuzzy", International Journal of Modern Education and Computer Science (IJMECS), vol.4, no.7, pp.42-49, 2012. DOI:10.5815/ijmecs.2012.07.06

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