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dc.contributor.authorNorasmadi, Abdul Rahim
dc.contributor.authorPaulraj, Murugesa Pandiyan, Assoc. Prof. Dr.
dc.contributor.authorAdom, Abdul Hamid, Prof. Dr.
dc.contributor.authorSathishkumar, Sundararaj
dc.date.accessioned2013-10-21T04:09:15Z
dc.date.available2013-10-21T04:09:15Z
dc.date.issued2012-06-18
dc.identifier.citationp. 702 - 713en_US
dc.identifier.isbn978-967-5760-11-2
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/28997
dc.descriptionThe 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.abstractProfoundly 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.isoenen_US
dc.publisherUniversiti Malaysia Perlis (UniMAP)en_US
dc.relation.ispartofseriesProceedings of the The 2nd International Malaysia-Ireland Joint Symposium on Engineering, Science and Business 2012 (IMiEJS2012);
dc.subjectVehicle noise classificationen_US
dc.subjectMulti-classifier systemen_US
dc.subjectMultilayer perceptronen_US
dc.subjectEnsemble decisionen_US
dc.titleMulti-classifier system for moving vehicles classification based on spectral bands energyen_US
dc.typeWorking Paperen_US
dc.contributor.urlnorasmadi@unimap.edu.myen_US


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