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Prediction of Corrosion Behavior of Nonferrous Metals in Seawater with ANN |
Dawei Cui;Leyun Lin;Yuehong Zhao |
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Abstract Set up an artificial neural net and train it with the data provided by four seawater corrosion experiment stations. After the succession of training , the net can predict any kind of metals corrosion status on 16years and the comparative error is not beyond 20 percent. Compare with the way of function regression, this result is more accurate. The net can also trained with the anomaly data that can not regress to any function and the net can make an accurate prediction.
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Received: 27 March 2003
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