Transactions of Nonferrous Metals Society of China The Chinese Journal of Nonferrous Metals

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中国有色金属学报

ZHONGGUO YOUSEJINSHU XUEBAO

第28卷    第10期    总第235期    2018年10月

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文章编号:1004-0609(2018)-10-2103-09
基于人工神经网络模型的含锑硫化矿氧化浸出行为预测
田庆华1, 2, 3,洪建邦1,辛云涛1,郭学益1, 2, 3

(1. 中南大学 冶金与环境学院,长沙 410083;
2. 有色金属资源循环利用湖南省重点实验室,长沙 410083;
3. 有色金属资源循环利用湖南省工程研究中心,长沙 410083
)

摘 要: 锑的浸出率是氧化处理含锑硫化矿时的重要结论指标,在氧化浸出过程中通过条件控制来得到更好的浸出率具有十分重要的意义,为了模拟和预测含锑硫化矿的氧化浸出过程,用人工神经网络模型对浸锑过程进行模拟,建立起单隐层8节点的“5-8-1型”误差逆向传播神经网络模型,所建人工神经网络模型可以对反应过程做出有效的模拟和预测,实验值与预测值的相关系数可达99%以上。并根据所建神经网络模型中不同输入量在网络中节点权重的不同,得出相关条件因素对锑浸出率的相对重要性从高到低依次为:盐酸浓度,反应温度,搅拌速度,液固比,反应时间。

 

关键字: 人工神经网络;浸锑过程;预测;相关系数;相对重要性

Prediction for oxidation leaching behavior of antimony containing sulfide ore based on artificial neural network model
TIAN Qing-hua1, 2, 3, HONG Jian-bang1, XIN Yun-tao1, GUO Xue-yi1, 2, 3

1. School of Metallurgy and Environment, Central South University, Changsha 410083, China;
2. Hunan Key Laboratory of Nonferrous Metal Resources Recycling, Changsha 410083, China;
3. Hunan Engineering Research Center of Nonferrous Metal Resources Recycling, Changsha 410083, China

Abstract:The leaching rate of antimony is an important index for the treatment of antimony sulfide ore. It is very important to obtain better leaching rate through conditional control in the process of oxidation leaching. In order to simulate and predict the oxidation leaching process of antimony containing sulfide ore, BP Neural network model was used to simulate the leaching process of antimony, and a 5-8-1 type model was established. The neural network model could predict the leaching efficiency of antimony in the process exactly, the correlation coefficient between experimental data and predicted data could reach 99%. According to the weights of inputs in the neural network model, the importances of different impacts are in the descending order: HCl concentration, temperature, stirring speed, liquid to solid ratio, time.

 

Key words: BP neural network model; leaching process of antimony; prediction; correlation coefficient; relative importance

ISSN 1004-0609
CN 43-1238/TG
CODEN: ZYJXFK

ISSN 1003-6326
CN 43-1239/TG
CODEN: TNMCEW

主管:中国科学技术协会 主办:中国有色金属学会 承办:中南大学
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