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|Title: ||Comparison of classifying the material mechanical properties by using k-Nearest Neighbor and Neural Network Backpropagation|
|Authors: ||Intan Maisarah, Abd Rahim|
Sazali, Yaacob, Prof. Dr.
|Keywords: ||k-Nearest Neighbor (k-NN);Neural network;Material mechanical properties|
|Issue Date: ||Mar-2011|
|Publisher: ||Science Academy|
|Citation: ||International Journal of Research and Reviews in Artificial Intelligence, vol. 1(1), 2011, pages 7-11|
|Abstract: ||This paper present a development of a system with non-destructive testing on the material to define the mechanical
properties of material. The experimental and testing of the material mechanical properties using vibration technique could
determine the natural frequencies, the damping ratio and mode shapes of the structure. However, in this study, we only
considering the natural frequencies and its amplitude of the material as the input data needed for training. As an extension for
the study, the input data tested with various method of classifier. The k-Nearest Neighbor classifier and artificial neural
network with Levenberg-Marquardt Backpropagation are developed to work as a system to classify the materials tested
according to their mechanical properties. The result from the classification system shows that k-NN is giving the accuracy of
99.79783 % with the k value of 1 and in the other hand, Levenberg-Marquardt Backpropagation is giving the best classification rate of 99.86%.|
|Description: ||Link to publisher's homepage at http://www.sciacademypublisher.com|
|Appears in Collections:||School of Mechatronic Engineering (Articles)|
Sazali Yaacob, Prof. Dr.
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