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《CORRSION SCIENCE AND PROTECTION TECHNOLOGY》 1995-03
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NEURAL NETWORK APPROACH IN RESEARCH OF METAL CORROSION IN SOIL

GUO Zhihu;JIN Minghui;GUI Xiuwen; MENG Xialan; XING Zhengliang ;LUO Yi(HuaZhong University of Science and Technologe, Wuhan 430074)  
This paper introduce neural network approach to study the non-linear reationshipbetween the physical and chemical properties and corrosion rate of carbon steel in soil from the collected corrosion data. The corrosion rate of carbon steel in soil can be predicted by trained neural nerwork. In the study, a neural network with 5-8-1 structure was used. The learning algorithm is BP (back-propagation) algorithm. As a result, H2O and Cl-ion in soil are dominant factors influencing corrosion of carbon steel.
【Fund】: 国家自然科学基金
【CateGory Index】: TG172.4
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