An enhanced feed-forward neural networks and a rule-based algorithm for predictive modelling of students' academic performance
Feed-forward Neural Networks, is a multilayer perceptron and a network structure capable of modelling the class prediction as a nonlinear combination of the inputs. The network has proven its suitability in solving several complex tasks. But sometimes, it has challenges of over-fitting, especially w...
Main Author: | Raheem, Ajiboye Adeleke |
---|---|
Format: | Thesis |
Language: | English |
Published: |
2016
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/15251/1/An%20enhanced%20feed-forward%20neural%20networks%20and%20a%20rule-based%20algorithm%20for%20predictive%20modelling%20of%20students%27%20academic%20performance.pdf |
Similar Items
-
Using an Enhanced Feed-Forward Neural Network Technique for Prediction of Students' Performance
by: Ajiboye, Adeleke Raheem, et al.
Published: (2015) -
Investigating digital watermark dynamics on carrier file by feed-forward neural network
by: Zeki, Akram M., et al.
Published: (2013) -
Using an Enhanced Feed-Forward BP Network for Predictive Model Building From Students’ Data
by: Ajiboye, Adeleke Raheem, et al.
Published: (2015) -
Enhancing Academic Excellence in a Malaysian Secondary School Via The Development of Strategic Study Orientation Skills
Devices
by: Mohd Ghani, Awang, et al.
Published: (2014) -
ASN academic social network for UMP
by: Yeoh, Boon Tiam
Published: (2014)