Title of article
Forecasting Number of Students Applicant for Courses by Artificial Neural Networks
Author/Authors
Pouramini، Jafar نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2014
Pages
8
From page
263
To page
270
Abstract
Forecasting the number of students who are going to take a special course in next semester in Computer Engineering field at Payam Noor University is the subject. To do this, many neural network structures have been tested with MATLAB software by existing data and were compared to real data, networks like feedforward backpropagation 3 and 4-layared, RBF network, etc. To achieve a network with optimum structure, various parameters and criteria like MAE1, MSE2 and MSEREG3, have been examined. At last, a 3-layered feedback neural network in the form of 20-n-1 was chosen for this problem. Comparing experiential results with real data, it is shown that the obtained model can effectively forecast enrolments of students. So it can be used for forecasting tasks especially when a forecast with high accuracy is needed.
Journal title
The Journal of Mathematics and Computer Science(JMCS)
Serial Year
2014
Journal title
The Journal of Mathematics and Computer Science(JMCS)
Record number
1435480
Link To Document