ANN modeling of anticorrosive performance of paint systems on steel
Publish Year: 1397
Type: Conference paper
Language: English
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IMES12_070
Index date: 1 May 2019
ANN modeling of anticorrosive performance of paint systems on steel abstract
In this investigation, the corrosion behavior of 1020 steel plates in term of corrosion potential wasmodeled using the ANN approach. Input variables were the surface pre-treatments, anticorrosive coatingsand the time of immersing in the corrosive environment. feedforward multi-Layer perceptron neuralnetwork was used. The reliability and speed of Levenberg–Marquardt Scaled conjugate gradient ,and Resilient backpropagation algorithms were also compared, and it was concluded that theLevenberg–Marquardt is the most accurate and the fastest algorithm for modeling. The results showedthat the estimated corrosion potentials of samples are in good agreement with the actual data.
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ANN modeling of anticorrosive performance of paint systems on steel authors
Morteza Azarbarmas
Assistant Prof. Faculty of Materials Engineering, Sahand University of Technology
Seyed Saiad Mirjavadi
M.S. School of Mechanical Engineering, College of Engineering, University of Tehran
Ali Ghasemi
Ph.D. Department of Mechanical Engineering, Faculty of Engineering, Islamic Azad University