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A. Martin, V. Prasanna Venkatesan et al, “To find the most impact financial features for bankruptcy model using genetic algorithm”, International Conference on Advances in Engineering and Technology, (ICAET-2011), May 27-28, 2011.

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Article

An Analysis of Students Performance Using Genetic Algorithm

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

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


Journal of Computer Sciences and Applications. 2013, Vol. 1 No. 4, 75-79
DOI: 10.12691/jcsa-1-4-3
Copyright © 2013 Science and Education Publishing

Cite this paper:
T. Miranda Lakshmi, A. Martin, 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.

Correspondence to: A. Martin, Department of Banking Technology, Pondicherry University, Puducherry, India. Email: jayamartin@yahoo.com

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.

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