Predicting the End Temperature of Molten Steel Using CBR
Year: 2012
Type: article
Abstract: Steel is a kind of important material. The accurate control about the end temperature of molten steel has significant impact on the quality of steel material. Case Based Reasoning (CBR) is used to predict the end temperature of molten steel in Argon Oxygen Decarburization (AOD). Grey Relational Degree (GRD) with different weights of attributes is adopted to calculate the similarity between cases. Analytic Hierarchy Process (AHP) is taken to determine the weights of attributes. Multiple Linear Regression (MLR) is applied to compute the relative weight of two different attributes for AHP. Two methods, CBR using AHP with Equal Weights (CBR_AHP_EW) and CBR using AHP with Different Weights (CBR_AHP_DW), are employed to for a comparison. The results show that CBR_AHP_DW is effective in predicting the end temperature of molten steel in AOD and CBR_AHP_DW outperforms CBR_AHP_EW.
Source: Applied Mechanics and Materials
Authors: De Hua Liu, Hong Bing Wang, An Jun Xu
Institution: University of Science and Technology Beijing
Language: English
Subfield: Metals and Alloys
Field: Materials Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W2005421493