Author(s):
Swati Jain, Vikas Kumar Jain, Sunil Kumar Kashyap, Sanjay Kumar
Email(s):
7sunilkumarkashyap@gmail.com
DOI:
10.5958/2321-581X.2017.00011.3 
Address:
Swati Jain1, Vikas Kumar Jain2, Sunil Kumar Kashyap3*, Sanjay Kumar1
1Department of Computer Science, Kalinga University, Raipur, Chhattisgarh, 492101, India
2Department of Chemistry, Government Engineering College, Raipur, Chhattisgarh, 492015, India
3Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology University, Vellore, Tamil Nadu, India, 632014
*Corresponding Author
Published In:
Volume - 8,
Issue - 2,
Year - 2017
ABSTRACT:
The data of student’s academic performance is studied as the application of fuzzy-genetic(FG) approach. Discrete and continuous data interpretation are overviewed by the linguistic classes and then its representation over the fuzzy-genetic algorithm in this chapter. This dual method has the advantages are noticed as class-variable transformation, language-number generalisation and characteristic-operation simulation. Fuzzy-genetic algorithm is a tool to study the data over the representation of randomness to weight. Hence the data represents as the discrete classes by itself as the self-organized operator under the fuzzy-genetic technique.
Cite this article:
Swati Jain, Vikas Kumar Jain, Sunil Kumar Kashyap, Sanjay Kumar. Academic Data Modelling based on Fuzzy-Genetic Algorithm. Research J. Engineering and Tech. 2017; 8(2): 71-72. doi: 10.5958/2321-581X.2017.00011.3
Cite(Electronic):
Swati Jain, Vikas Kumar Jain, Sunil Kumar Kashyap, Sanjay Kumar. Academic Data Modelling based on Fuzzy-Genetic Algorithm. Research J. Engineering and Tech. 2017; 8(2): 71-72. doi: 10.5958/2321-581X.2017.00011.3 Available on: https://ijersonline.org/AbstractView.aspx?PID=2017-8-2-1