@article{jcsa2013143,
author={{Lakshmi, T. Miranda and Martin, A. and Venkatesan, V. Prasanna},
title={An Analysis of Students Performance Using Genetic Algorithm},
journal={Journal of Computer Sciences and Applications},
volume={1},
number={4},
pages={75--79},
year={2013},
url={http://pubs.sciepub.com/jcsa/1/4/3},
issn={2328-725X},
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 genetic algorithm.},
doi={10.12691/jcsa-1-4-3}
publisher={Science and Education Publishing}
}