中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
The improvement of regular solution model based on genetic algorithm and neural network and its application in binary slag systems

文献类型:期刊论文

作者Wu Ling; Jiang Zhouhua; Gong Wei; Liang Lianke
刊名ACTA METALLURGICA SINICA
出版日期2008
卷号44期号:7页码:799-802
关键词slag regular solution model activity neural network genetic algorithm
ISSN号0412-1961
其他题名THE IMPROVEMENT OF REGULAR SOLUTION MODEL BASED ON GENETIC ALGORITHM AND NEURAL NETWORK AND ITS APPLICATION IN BINARY SLAG SYSTEMS
英文摘要A real solution activity model was introduced by improving the components interaction energy in regular solution model with genetic algorithm (GA) and neural network (NN) and the activities of components in MnO-SiO2 and CaO-Al2O3 binary systems were estimated by this model. Due to the different properties between real solution and regular solution, it is proved that the interaction energy Omega(ij) is the function of temperature and composition, and Omega(ij) not equal Omega(ij) at the same temperature and composition. With the comparison of results received by calculation and previous studies, the improved model has a high nonlinear fitting capability, so it can be used to accurately predict the activity of solution component.
语种英语
CSCD记录号CSCD:3355058
源URL[http://ir.imr.ac.cn/handle/321006/142470]  
专题金属研究所_中国科学院金属研究所
作者单位中国科学院金属研究所
推荐引用方式
GB/T 7714
Wu Ling,Jiang Zhouhua,Gong Wei,et al. The improvement of regular solution model based on genetic algorithm and neural network and its application in binary slag systems[J]. ACTA METALLURGICA SINICA,2008,44(7):799-802.
APA Wu Ling,Jiang Zhouhua,Gong Wei,&Liang Lianke.(2008).The improvement of regular solution model based on genetic algorithm and neural network and its application in binary slag systems.ACTA METALLURGICA SINICA,44(7),799-802.
MLA Wu Ling,et al."The improvement of regular solution model based on genetic algorithm and neural network and its application in binary slag systems".ACTA METALLURGICA SINICA 44.7(2008):799-802.

入库方式: OAI收割

来源:金属研究所

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