Examining Genetic Algorithms as an effective Computational tool in Education-Domain
Amritpal Singh, Gurjit Singh "Examining Genetic Algorithms as an effective Computational tool in Education-Domain". International Journal of Computer Trends and Technology (IJCTT) V34(3):156-159, April 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract -
This paper employs Genetic algorithms
(GA`s) for the enhancement of computational
capabilities to achieve reduction in time
complexities. These algorithms can be applied on
diverse problems related to different fields like Civil
Engineering, Bio Informatics, Bio Technology, Basic
Sciences etc. Solution is evident and already
provided by the nature; but how to look for it,
depends upon individual. So, learning inspired from
natural phenomenon can help in improving quality
of higher education. Genetic algorithms mimic
natural process of preserving the best and still try to
improve solutions at each step. This paper focuses
on less amount of time taken by these algorithms for
performing calculations and generating results as
compared to conventional techniques. These can be
implemented very efficiently at various levels to
deliver quality education.
References
[1] Sanjay S, Pradeep S , Manikanta V , Kumara S.S and
Harsha P, Genetic Algorithm Based Approach for the
Selection of Projects In Public R&D Institutions,Indian
Journal of Computer Science and Engineerin, 2011
[2] Xing Lining, Chen Yingwu, Cai Huaiping, and Tao
Fengyuan, The intelligent genetic algorithm with solving
the whole optimited problems, Journal of System
Simulation,2006.
[3] S. Vishnupriyan, L. Govindarajan, G. Prabhakaran & K.P.
Ramachandran, Quality Improvement in Higher Education
through Normalization of Student Feedback data Using
Evolutionary Algorithm, The International Journal of
Applied Management and Technology, Vol 6, Num 3
[4] Simon mardle & Sean pascol.( 1999) .An overview of
genetic algorithms for the solution of optimization
problems, Computers in Higher Education Economics
Review, 13(1),pp.16-20.
[5] Ahmed A A Radwan; Abdel Mgeid A Ali;Bahgat A Abdel
Latef & Osman A Sadek. (2006).Using genetic algorithm
to improve information retrieval systems, Proceedings of
the World Academy of Science Engineering and
Technology, 17, pp.6-12.
[6] Cong Mingyu and Wang Liping, The intelligentized genetic
algorithm , High Technology Letters, 2003.
[7] Fernando G. Lobo, David E. Goldberg, Martin Pelikan,
Time complexity of genetic algorithms on exponentially
scaled problem, 1991, pp. 51-58s
[8] Sergi Perez. Apply Genetic Algorithm to the learning phase
of Neural Network, Department of Mechanical and
Aerospace Engineering, University of California, Irvine
[9] Goldberg D E, Genetic Algorithms: In search, optimization
and machine learning, New York: Addison-Wesley
Publishing Co. Inc.,1989, pp. 59-75.
[10] Donald J. Berndt and Alison Watkins, Investigating the
Performance of Genetic Algorithm-Based Software Test
Case Generation, Eighth IEEE International Symposium
on High Assurance Systems Engineering (HASE’04)
[11] E.hussein, Sherif, and Mahmoud Abo El-Nasr. "Resources
Allocation in Higher Education Based on System
Dynamics and Genetic Algorithms." International Journal
of Computer Applications IJCA 77.10 (2013): 40-48. Web.
[12] Tian, Yu Guang, and Liang Ma. "Research on Limited
Resources Optimal Allocation Model." Proceedings of the
2015 International Conference on Education,
Management, Information and Medicine (2015). Web.
[13] Zhu, Yulan, Linlin Zhang, and Shaorong Sun. "Class Hour
Allocation Optimization Model between E-education and
Traditional Education in the Process of Higher Vocational
Technology Education." 2011 International Conference on
E-Business and E-Government (ICEE) (2011). Web.
Keywords
Genetic Algorithm, Neural Networks,
Education-domain, Computational tool.