| 人工神经网络研究氨配合法制活性氧化锌 |
| |
| 引用本文： | 曾之平,赵明蕊,赵红坤,唐亮,王艳军. 人工神经网络研究氨配合法制活性氧化锌[J]. 无机盐工业, 2004, 36(4): 34-36 |
| |
| 作者姓名： | 曾之平 赵明蕊 赵红坤 唐亮 王艳军 |
| |
| 作者单位： | 郑州大学化工学院,河南,郑州,450002 |
| |
| 摘 要： | 采用工业氧化锌生产中回收的烟道灰为原料，加入过氧化氢进行氧化，提高氧化锌浸取率，并对氨配合法制备活性氧化锌工艺过程中影响浸取率的因素进行研究，用BP(误差反向传播)神经网络对结果进行优化，建立了浸取率的神经网络模型，得到了浸取工艺的最佳工艺条件。结果表明，在此工艺条件下，浸取率可达88.1％。
|
| 关 键 词： | 人工神经网络 氨配合法 活性氧化锌 |
| 文章编号： | 1006-4990(2004)04-0034-03 |
| 修稿时间： | 2004-02-26 |
Application of artificial neural networks in preparing activated zinc oxide by ammonia complex leaching technique |
| |
| Zeng Zhiping,Zhao Mingrui,Zhao Hongkun,Tang Liang,Wang Yanjun. Application of artificial neural networks in preparing activated zinc oxide by ammonia complex leaching technique[J]. Inorganic Chemicals Industry, 2004, 36(4): 34-36 |
| |
| Authors: | Zeng Zhiping Zhao Mingrui Zhao Hongkun Tang Liang Wang Yanjun |
| |
| Abstract: | Using the stack ash produced from industrial zinc oxide production as raw material,adding H_2O_2 for oxidation,the activated zinc oxide can be prepared by ammonia complex leaching method.The factors of influencing leaching rate are studied.The test result is optimized by BP-Artificial Neural Networks(BP-ANN),the model of BP-ANN for the leaching process is established and the optimum conditions in leaching process are obtained.The results show that the leaching rate under those conditions can reach 88.1%. |
| |
| Keywords: | artificial neural network ammonia complex method activated zinc oxide |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
