个人信息Personal Information
副教授
硕士生导师
性别:女
毕业院校:大连理工大学
学位:博士
所在单位:控制科学与工程学院
电子邮箱:liu_ying@dlut.edu.cn
Soft computing for overflow particle size in grinding process based on hybrid case based reasoning
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论文类型:期刊论文
发表时间:2015-02-01
发表刊物:APPLIED SOFT COMPUTING
收录刊物:EI、SCIE
卷号:27
期号:27
页面范围:533-542
ISSN号:1568-4946
关键字:Overflow particle size; Soft computing; Case based reasoning; Community finding
摘要:The overflow particle size of cyclone is one of the most significant performance indices in the process of ore grinding. Given the measuring difficulty under the current industrial conditions, a hybrid method, which combines community finding (CF) of a complex network with case-based reasoning (CBR) is proposed in this study. The CF method with a new evaluation criterion for the vertex combination degree is designed to select the typical cases from the constructed communities, and a k-nearest neighbors (k-NN) based strategy with multi-similarity threshold is proposed in the case retrieval process. To verify the effectiveness of the proposed method, a number of comparative simulations by using the real-world data coming from a copper-molybdenum concentration plant are carried out, and the results indicate that the proposed method can provide a good measure quality for the industrial application. (C) 2014 Elsevier B. V. All rights reserved.