Abstract
The main consequences of corrosion are the costs derived from both the maintenance tasks as from the public safety protection. In this sense, artificial intelligence models are used to determine pitting corrosion behaviour of stainless steel. This work presents the C-MANTEC constructive neural network algorithm as an automatic system to determine the status pitting corrosion of that alloy. Several classification techniques are compared with our proposal: Linear Discriminant Analysis, k-Nearest Neighbor, Multilayer Perceptron, Support Vector Machines and Naive Bayes. The results obtained show the robustness and higher performance of the C-MANTEC algorithm in comparison to the other artificial intelligence models, corroborating the utility of the constructive neural networks paradigm in the modelling pitting corrosion problem.
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Urda, D., Luque, R.M., Jiménez, M.J., Turias, I., Franco, L., Jerez, J.M. (2013). A Constructive Neural Network to Predict Pitting Corrosion Status of Stainless Steel. In: Rojas, I., Joya, G., Gabestany, J. (eds) Advances in Computational Intelligence. IWANN 2013. Lecture Notes in Computer Science, vol 7902. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38679-4_7
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DOI: https://doi.org/10.1007/978-3-642-38679-4_7
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