作者：KOUTA UCHIYAMA;JUN KOBAYASHI;NOZOMU UCHIDA;
作者單位：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
起頁：120
止頁：120
分類號：TQ175
語種：英文
關鍵詞：
內容簡介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.
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