Title :
Predicting the Corrosion Rates of Steels in Sea Water Using Artificial Neural Network
Author :
You, Wei ; Liu, Yaxiu
Author_Institution :
Dept. of Mech. & Electr. Eng., North China Inst. of Sci. & Technol., Beijing
Abstract :
Back-propagation artificial neural network was developed to predict the corrosion rates of steels in sea water. Leave-one out method was used to train the ANN model. Test results showed that the prediction performance of the ANN model is satisfactory: the scatter dots distribute along the 0__45deg diagonal line in the scatter diagram, the values of statistical criteria are 1.3498 muAldrcm-2 (MSE), 10.85%(MSRE), and 1.8668(VOF) respectively. Moreover, the ANN model was used to analyse the quantitative effects of parameters of environment in sea water on the corrosion rate, results showed that the corrosion rate decreases with the increase of temperature and pH value, increase with the increase of oxygen content and oxidation-reduce potent, and change little with the increase of salt content.
Keywords :
backpropagation; corrosion; materials science computing; neural nets; oxidation; seawater; steel; back-propagation artificial neural network; corrosion rates; oxidation-reduce potent; oxygen content; pH value; salt content; sea water; steels; Application software; Artificial neural networks; Computer networks; Corrosion; Electronic mail; Ocean temperature; Predictive models; Scattering; Steel; Testing;
Conference_Titel :
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-0-7695-3304-9
DOI :
10.1109/ICNC.2008.481
