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Analysis of Hybrid Neural Network for Improved Performance

by Zainab Khalid Awan, Aamir Khan, Anam Iftikhar, Sadia Zahid, Anam Malik
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 50 - Number 1
Year of Publication: 2012
Authors: Zainab Khalid Awan, Aamir Khan, Anam Iftikhar, Sadia Zahid, Anam Malik
10.5120/7733-0681

Zainab Khalid Awan, Aamir Khan, Anam Iftikhar, Sadia Zahid, Anam Malik . Analysis of Hybrid Neural Network for Improved Performance. International Journal of Computer Applications. 50, 1 ( July 2012), 8-17. DOI=10.5120/7733-0681

@article{ 10.5120/7733-0681,
author = { Zainab Khalid Awan, Aamir Khan, Anam Iftikhar, Sadia Zahid, Anam Malik },
title = { Analysis of Hybrid Neural Network for Improved Performance },
journal = { International Journal of Computer Applications },
issue_date = { July 2012 },
volume = { 50 },
number = { 1 },
month = { July },
year = { 2012 },
issn = { 0975-8887 },
pages = { 8-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume50/number1/7733-0681/ },
doi = { 10.5120/7733-0681 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:47:09.225094+05:30
%A Zainab Khalid Awan
%A Aamir Khan
%A Anam Iftikhar
%A Sadia Zahid
%A Anam Malik
%T Analysis of Hybrid Neural Network for Improved Performance
%J International Journal of Computer Applications
%@ 0975-8887
%V 50
%N 1
%P 8-17
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper we take a close look at the Hybrid Neural Network Model. Hybrid model is attained by combining two Artificial Neural Networks (ANNs). In which the first model is used to perform the feature extraction task and the second one performs prediction task. This paper explores the classifying ability of the proposed hybrid model. We analyze the performance of the model, which is a compound characteristic, of which the prediction accuracy is the most important component. If the prediction accuracy of the model can be increased it will result into enhanced performance of the model. The model that has been built is under the umbrella of pattern recognition and incorporates some of the data mining techniques. Kernel Principal Component Analysis (KPCA) has been implemented in the pre-processing stage for easier subsequent analysis. By the end of the paper, the key factors that enhance the accuracy of the model have been identified and their role explained. It also has been shown that single ANN model's performance deteriorates on an unseen problem much more as compared to the hybrid model. The aim is to provide a model having better performance and accuracy. The paper focuses on the real world applications of the model.

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Index Terms

Computer Science
Information Sciences

Keywords

Unseen Test Set (UTS) Seen Test Set (STS)

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