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Evaluation of Students Performance using Hierarchical Fuzzy Inference System

by Abdulkadir Abdullahi, Wang Peng, Abdullahi S. Saheed
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 177 - Number 23
Year of Publication: 2019
Authors: Abdulkadir Abdullahi, Wang Peng, Abdullahi S. Saheed
10.5120/ijca2019919690

Abdulkadir Abdullahi, Wang Peng, Abdullahi S. Saheed . Evaluation of Students Performance using Hierarchical Fuzzy Inference System. International Journal of Computer Applications. 177, 23 ( Dec 2019), 39-45. DOI=10.5120/ijca2019919690

@article{ 10.5120/ijca2019919690,
author = { Abdulkadir Abdullahi, Wang Peng, Abdullahi S. Saheed },
title = { Evaluation of Students Performance using Hierarchical Fuzzy Inference System },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2019 },
volume = { 177 },
number = { 23 },
month = { Dec },
year = { 2019 },
issn = { 0975-8887 },
pages = { 39-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume177/number23/31040-2019919690/ },
doi = { 10.5120/ijca2019919690 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:46:44.651789+05:30
%A Abdulkadir Abdullahi
%A Wang Peng
%A Abdullahi S. Saheed
%T Evaluation of Students Performance using Hierarchical Fuzzy Inference System
%J International Journal of Computer Applications
%@ 0975-8887
%V 177
%N 23
%P 39-45
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Fuzzy Inference Systems (FIS) has often been used to evaluate performance using few input variables as a result of fear for rules explosion. This problem is solved using Hierarchical Fuzzy Inference System (HFIS); a divide-and-conquer approach that drastically reduce the number of rules at the same time preserved the fuzzy logic reasoning. As a result, this study explore the potential of this tool in details by applying it to evaluate students’ exam records. The proposed model is compared to classical one and results show that HFIS is more promising from the perspective of simplicity and precision. However, for optimum results, the study suggests training FIS with neural networks and emerging optimization algorithms.

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Index Terms

Computer Science
Information Sciences

Keywords

Hierarchical Fuzzy Inference System (HFIS) Fuzzy logic Membership function student performance MATLAB

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