On the use of artificial neural networks as quality control tool

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ConferenceCANCAM 2007 Proceedings: 03 June 2007, Toronto, Ontario
Pages594595; # of pages: 2
AbstractThis paper presents the use of artificial neural networks (ANN) technique as a potential quality control tool for detecting erroneous data in databases. Inconsistent behaviour observed while constructing an ANN application for a resilient modulus database indicated the possible existence of incorrect entries in laboratory-generated data set. Subsequent removal of suspected faulty data was made to assess the prediction capabilities of the developed network and enabled the determination of the optimum number of nodes to be used in the hidden layer.
Publication date
AffiliationNRC Institute for Research in Construction; National Research Council Canada
Peer reviewedYes
NRC number49224
NPARC number20378291
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Record identifierbff017af-d5ff-46dc-b2bc-d0f0722d85e2
Record created2012-07-24
Record modified2016-05-09
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