Classification of data using multilayered perceptron neural network

Neural networks become widely in its application to help human in the identification process nowadays. However, to have a neural network system which is able to provide 100% accuracy performance and providing optimum value structure is difficult. In this project, multilayer perceptron neural network...

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Bibliographic Details
Main Authors: Joret, Ariffuddin, Zainudin, Siti Zuraidah, Mat Isa, Nor Ashidi, Abdullah, Jiwa, Zamli, Kamal Zuhairi, Abdullah, Mohammad Faiz Liew, Ponniran, Asmarashid
Format: Conference or Workshop Item
Published: 2012
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Online Access:http://eprints.uthm.edu.my/6078/
http://eprints.uthm.edu.my/6078/1/Classification_of_Data_Using_Multilayered.pdf
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Summary:Neural networks become widely in its application to help human in the identification process nowadays. However, to have a neural network system which is able to provide 100% accuracy performance and providing optimum value structure is difficult. In this project, multilayer perceptron neural network with Backpropagation as its algorithm has been trained and tested for its accuracy. The multilayer perceptron neural network has been tested using gravel data which have been categorized into 6 categories and gives 82.90% of the network classifying performance for optimum structure with 16 hidden node.