文献类型：会议论文

英文题名：Neural prediction model for microwave calcination-sulphuric acid leaching of germanium from zinc oxide dust

作者：Wang, Wankun Wang, Fuchun Lu, Fanghai

第一作者：Wang, Wankun;王万坤

通信作者：Wang, WK[1];Wang, WK[2]

机构：[1]Key Lab Light Met Mat Proc Technol Guizhou Prov, Guiyang 550003, Guizhou, Peoples R China;[2]Guizhou Inst Technol, Chool Mat & Met Engn, Guiyang 550003, Guizhou, Peoples R China

第一机构：Key Lab Light Met Mat Proc Technol Guizhou Prov, Guiyang 550003, Guizhou, Peoples R China

通信机构：corresponding author), Key Lab Light Met Mat Proc Technol Guizhou Prov, Guiyang 550003, Guizhou, Peoples R China;corresponding author), Guizhou Inst Technol, Chool Mat & Met Engn, Guiyang 550003, Guizhou, Peoples R China.|贵州理工学院;

会议论文集：3rd International Forum on Energy, Environment Science and Materials (IFEESM)

会议日期：NOV 25-26, 2017

会议地点：Shenzhen, PEOPLES R CHINA

语种：英文

外文关键词：zinc oxide dust; germanium; microwave calcinations; artificial neural network

年份：2017

摘要：Based on the study of artificial neural network, the neural model was established for the prediction of germanium extraction from zinc oxide dust by microwave calcination-sulphuric acid leaching. Microwave heating temperature, liquid-solid ratio, leaching time, initial concentration of sulphuric acid and leaching temperature were the significant factors for the process. The results indicated that the neural network prediction model was reliable, the forecast and actual values fitted well. The model could be used to predict the regeneration experiments with high credibility and practical significance. The accuracy of convergence of the model has reached 10(-5).