Journal of Computer Sciences and Applications
ISSN (Print): 2328-7268 ISSN (Online): 2328-725X Website: http://www.sciepub.com/journal/jcsa Editor-in-chief: Minhua Ma, Patricia Goncalves
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Journal of Computer Sciences and Applications. 2013, 1(4), 75-79
DOI: 10.12691/jcsa-1-4-3
Open AccessArticle

An Analysis of Students Performance Using Genetic Algorithm

T. Miranda Lakshmi1, A. Martin2, and V. Prasanna Venkatesan2

1Department of Computer Science, Bharathiyar University, Coimbatore, India

2Department of Banking Technology, Pondicherry University, Puducherry, India

Pub. Date: May 31, 2013

Cite this paper:
T. Miranda Lakshmi, A. Martin and V. Prasanna Venkatesan. An Analysis of Students Performance Using Genetic Algorithm. Journal of Computer Sciences and Applications. 2013; 1(4):75-79. doi: 10.12691/jcsa-1-4-3

Abstract

Genetic algorithm plays a significant role, as search techniques for handling complex spaces, in many fields such as artificial intelligence, engineering, robotic, etc. The genetic processes on the natural evolution principles of populations have been fairly successful at solving problems and produce optimized solution from generation to generation. This is applied in students’ quantitative data analysis to identify the most impact factor in their performance in their curriculum. The results will help the educational institutions to improve the quality of teaching after evaluating the marks achieved by the students’ in academic career. This student analysis model considers the quantitative factors such as theoretical, mathematical, practical, departmental and other departmental marks to find the most impacting factor using real genetic algorithm.

Keywords:
students’ performance quantitative factors real genetic algorithm impact factor evaluation results

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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