Article citationsMore >>

Karamouzis, S. T and Vrettos, A. (2009) Sensitivity Analysis of neural Network parameters for identifying the factors for college students’ success. World Congress on Computer Science and Information Engineering. 2009, Los Angeles, USA, March 31th –April 2nd, 2009, pp. 671-675.

has been cited by the following article:

Article

Of Students Academic Performance Rates Using Artificial Neural Networks (ANNs)

1Department of Mathematics, Computer Science, Statistics and Informatics, Federal University Ndufu-Alike Ikwo

2Department of Statistics, University of Nigeria, Nsukka


American Journal of Applied Mathematics and Statistics. 2015, Vol. 3 No. 4, 151-155
DOI: 10.12691/ajams-3-4-3
Copyright © 2015 Science and Education Publishing

Cite this paper:
O. C. Asogwa, A. V.Oladugba. Of Students Academic Performance Rates Using Artificial Neural Networks (ANNs). American Journal of Applied Mathematics and Statistics. 2015; 3(4):151-155. doi: 10.12691/ajams-3-4-3.

Correspondence to: O.  C. Asogwa, Department of Mathematics, Computer Science, Statistics and Informatics, Federal University Ndufu-Alike Ikwo. Email: qackasoo@yahoo.com

Abstract

A model based on the multilayer perception algorithm was programmed. The result from the test data evaluation showed that the programmed Artificial Neural Network model was able to correctly predict and classify the performance of students with Mean Correct Classification Rate CCR of 97.07%.

Keywords