Neural Network Prediction of Conversion Rate of TbFe2 Alloy Prepared by Reduction-Diffusion Process
文献类型：期刊论文
| 作者 | Guo Guangsi2; Wang Guangtai2; Cheng Yongjun1; Hu Xiaomei2 |
| 刊名 | RARE METAL MATERIALS AND ENGINEERING
 |
| 出版日期 | 2015 |
| 卷号 | 44期号:5页码:1104-1107 |
| 关键词 | CA-TB4O7-FE SYSTEM neural network prediction TbFe2 alloy rate of conversion |
| ISSN号 | 1002-185X |
| 其他题名 | Neural Network Prediction of Conversion Rate of TbFe2 Alloy Prepared by Reduction-Diffusion Process |
| 英文摘要 | A BP neural network was established based on the following main experiment parameters of producing TbFe2 alloy by reduction-diffusion process: reaction temperature, holding time, quantity of Ca and particle size of Fe. A simulation was conducted, and the rate of conversion of TbFe2 alloy was predicted. The neural network was simulated and tested by 44 groups of experimental data. It can be concluded that the neural network has good performance to predict the rate of conversion of TbFe2 alloy. The design and the application of this neural network can help to shorten the periodic time of experiments, lower the experimental cost, and optimize the preparation processes. |
| 资助项目 | [National Natural Science Foundation of China] |
| 语种 | 英语 |
| CSCD记录号 | CSCD:5418908 |
| 源URL | [http://ir.imr.ac.cn/handle/321006/156955]  |
| 专题 | 金属研究所_中国科学院金属研究所 |
| 作者单位 | 1.中国科学院金属研究所 2.沈阳理工大学 |
| 推荐引用方式 GB/T 7714 | Guo Guangsi,Wang Guangtai,Cheng Yongjun,et al. Neural Network Prediction of Conversion Rate of TbFe2 Alloy Prepared by Reduction-Diffusion Process[J]. RARE METAL MATERIALS AND ENGINEERING,2015,44(5):1104-1107. |
| APA | Guo Guangsi,Wang Guangtai,Cheng Yongjun,&Hu Xiaomei.(2015).Neural Network Prediction of Conversion Rate of TbFe2 Alloy Prepared by Reduction-Diffusion Process.RARE METAL MATERIALS AND ENGINEERING,44(5),1104-1107. |
| MLA | Guo Guangsi,et al."Neural Network Prediction of Conversion Rate of TbFe2 Alloy Prepared by Reduction-Diffusion Process".RARE METAL MATERIALS AND ENGINEERING 44.5(2015):1104-1107. |
入库方式： OAI收割
来源：金属研究所
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