eprintid: 630
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/06/30
datestamp: 2023-11-09 15:48:46
lastmod: 2023-11-09 15:48:46
status_changed: 2023-11-09 15:22:50
type: conference_item
metadata_visibility: show
creators_name: Hanif, N.H.H.M.
creators_name: Lan, W.H.
creators_name: Daud, H.B.
creators_name: Ahmad, J.
title: Classification of control measures for asthma using artificial neural network
ispublished: pub
keywords: Artificial Neural Network; Backpropagation network; Classification; Classification tasks; Control measures; Feedforward backpropagation; Matlab- software; Trained neural networks, Attitude control; Backpropagation; Graphical user interfaces; MATLAB; Network architecture; Radial basis function networks, Neural networks
note: cited By 2; Conference of IASTED International Conference on Artificial Intelligence and Applications, AIA 2009 ; Conference Date: 16 February 2009 Through 18 February 2009; Conference Code:79204
abstract: This project is to classify control measures of asthma using artificial neural networks. Asthma is a common disease throughout the whole world. Symptoms of asthma can range from mild to severe. The aim of this project is to classify different severity of asthma and the suitable control measures to overcome it. Neural network architectures were developed for the different severity of asthma. For this preliminary research, three different networks were developed, which are feed forward backpropagation network, Elman backpropagation network and radial basis function network. The most suitable control measures were obtained by training the constructed neural network architectures. The accuracy of the trained architectures was tested by inputting new sets of data to a created Graphical User Interface (GUI). Supervised learning was utilized for this purpose. Based on the works conducted, the radial basis function network achieves accuracy of 90 in classifying the control measures of asthma, which proves that a well trained neural network has a significant capability in classification tasks. To conduct the specified works, MATLAB software were extensively used.
date: 2009
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-74549123279&partnerID=40&md5=35a897d28ec9388f5f783fe720a981e4
full_text_status: none
publication: Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2009
place_of_pub: Innsbruck
pagerange: 163-168
refereed: TRUE
isbn: 9780889867802
citation:   Hanif, N.H.H.M. and Lan, W.H. and Daud, H.B. and Ahmad, J.  (2009) Classification of control measures for asthma using artificial neural network.  In: UNSPECIFIED.