Work

Students Classification With Adaptive Neuro Fuzzy

Year: 2012

Type: article

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.

Source: International Journal of Modern Education and Computer Science

DOI: 10.5815/ijmecs.2012.07.06

Authors: Mohammad Saber Iraji, Majid Aboutalebi, Naghi. R. Seyedaghaee, Azam Tosinia

Institutions: Islamic Azad University, Tehran, Islamic Azad University Sari Branch, Islamic Azad University, Aliabad Katoul

Language: English

Topic: Online Learning and Analytics

Subfield: Computer Science Applications

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: bronze

Funder: Islamic Azad University