PREDICTION OF STEEL ATMOSPHERIC CORROSION BY MEANS OF ARTIFICIAL INTELLIGENCE METHODS

被引：0
|
作者：
Jancikova, Zora [1 ]
Kreislova, Katerina [2 ]
Kostial, Pavel [1 ]
Ruziak, Ivan [1 ]
Bogar, Martin [1 ]
机构：
[1] VSB TU Ostrava, 17 Listopadu 15, Ostrava 70833, Czech Republic
[2] SVUOM Sro, Prague 17000 7, Czech Republic
来源：
METAL 2011: 20TH ANNIVERSARY INTERNATIONAL CONFERENCE ON METALLURGY AND MATERIALS | 2011年
关键词：
artificial neural networks; atmospheric corrosion; prediction; model;
D O I：
暂无
中图分类号：
TF [冶金工业];
学科分类号：
0806 ;
摘要：
Atmospheric corrosion of metal materials exposed under atmospheric conditions depends on various factors such as local temperature, relative humidity, amount of precipitation, pH of rainfall, concentration of main pollutants and exposition time. As these factors are very complex, exact relation for mathematical description of atmospheric corrosion of various metals are not known so far. Classical analytical and mathematical functions are of limited use to describe this type of strongly non-linear system depending on various meteorological-chemical factors and interaction between them and on material parameters. Nowadays there is certain chance to predict a corrosion loss of materials by artificial intelligence methods. The contribution deals with the use of artificial neural networks for prediction of steel atmospheric corrosion.
引用
收藏
页码：1201 / 1205
页数：5
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