Please use this identifier to cite or link to this item:
http://dspace.unimap.edu.my:80/xmlui/handle/123456789/28997
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Norasmadi, Abdul Rahim | - |
dc.contributor.author | Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr. | - |
dc.contributor.author | Adom, Abdul Hamid, Prof. Dr. | - |
dc.contributor.author | Sathishkumar, Sundararaj | - |
dc.date.accessioned | 2013-10-21T04:09:15Z | - |
dc.date.available | 2013-10-21T04:09:15Z | - |
dc.date.issued | 2012-06-18 | - |
dc.identifier.citation | p. 702 - 713 | en_US |
dc.identifier.isbn | 978-967-5760-11-2 | - |
dc.identifier.uri | http://dspace.unimap.edu.my/123456789/28997 | - |
dc.description | The 2nd International Malaysia-Ireland Joint Symposium on Engineering, Science and Business 2012 (IMiEJS2012) jointly organized by Universiti Malaysia Perlis and Athlone Institute of Technology in collaboration with The Ministry of Higher Education (MOHE) Malaysia, Education Malaysia and Malaysia Postgraduates Student Association Ireland (MyPSI), 18th - 19th June 2012 at Putra World Trade Center (PWTC), Kuala Lumpur, Malaysia. | en_US |
dc.description.abstract | Profoundly hearing impaired community cannot moderate wisely an acoustic noise emanated from moving vehicle in outdoor. They are not able to distinguish either type or distance of moving vehicle approaching from behind. Since, the hearing impaired encounter risky situation while they are in outdoor. In this paper, a simple system has been proposed for identify the type and distance of a moving vehicle using multi-classifier system (MCS). One-third octave filter bands approach have been used for extracting the significant feature from the noise emanated by the moving vehicle. The extracted features were associated with the type and distance of the moving vehicle and the MCS based on neural network model has been developed. The developed neural network model with same hidden neuron has been proposed for MCS. This network has been tested for single classifier and MCS. The developed MCS give a better classification accuracy compared to single classifier. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Universiti Malaysia Perlis (UniMAP) | en_US |
dc.relation.ispartofseries | Proceedings of the The 2nd International Malaysia-Ireland Joint Symposium on Engineering, Science and Business 2012 (IMiEJS2012); | - |
dc.subject | Vehicle noise classification | en_US |
dc.subject | Multi-classifier system | en_US |
dc.subject | Multilayer perceptron | en_US |
dc.subject | Ensemble decision | en_US |
dc.title | Multi-classifier system for moving vehicles classification based on spectral bands energy | en_US |
dc.type | Working Paper | en_US |
dc.contributor.url | norasmadi@unimap.edu.my | en_US |
Appears in Collections: | Conference Papers Abdul Hamid Adom, Prof. Dr. Paulraj Murugesa Pandiyan, Assoc. Prof. Dr. |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
pg 702 - 713.pdf | Access is limited to UniMAP community | 378.39 kB | Adobe PDF | View/Open |
Items in UniMAP Library Digital Repository are protected by copyright, with all rights reserved, unless otherwise indicated.