作者：KOUTA UCHIYAMA;JUN KOBAYASHI;NOZOMU UCHIDA;

作者单位：Nagaoka University of Technology, Nippon Steel Corp.;Nagaoka University of Technology, Nippon Steel Corp.;Nagaoka University of Technology, Nippon Steel Corp.

刊名：Journal of the Technical Association of Refractories

ISSN：0285-0028

出版年：2010-01-05

卷：30

期：2

起页：120

止页：120

分类号：TQ175

语种：英文

关键词：

内容简介

It is very important to understand the factors that affect the corrosion of MgO-C refractories during steel making to improve the efficiency of steelmaking. In this study, the wear factors were analyzed with the artificial neural network (ANN) method, which is a non-linear analyzing technique. The corrosion data used to construct the ANN were obtained from previously published studies. The final network model reproduced the experimental results satisfactorily and revealed new information from the data set used.