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计算机系统应用英文版:2017,26(10):251-255
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GA-ELM在硫铁矿制酸尾气SO2浓度预测的应用
(广西大学 电气工程学院, 南宁 530004)
Application of ELM in Prediction of SO2 Concentration of the Tail Gas in Producing Acid with Pyrite
(School of Electrical Engineering, Guangxi University, Nanning 530004, China)
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Received:June 29, 2016    
中文摘要: 基于对整个生产流程的管控,使硫铁矿生产硫酸尾气的SO2浓度达标排放,提出运用GA-ELM对制酸尾气SO2浓度进行建模预测.在硫铁矿制酸的生产过程中采集对尾气SO2浓度影响较大的关键点参数,运用GA-ELM神经网络对烟气制酸尾气SO2浓度进行预测.该方法在某厂实际检验,其预测结果与实际数据吻合度较高,对于调整和优化工艺指标和尾气达标排放起到很好的指导作用.
中文关键词: 尾气排放  SO2浓度  极限学习机  预测
Abstract:Based on the control of the whole production process, to make emissions of SO2 concentration conform to the standards in the production of sulfuric acid with pyrite, we propose prediction for SO2 concentration of tail gas with GA-ELM modeling. In the production of sulfuric acid by pyrite, we collect the key parameters with greater influence on the SO2 concentration of exhaust gas, and use GA-ELM neural network to predict the SO2 concentration while producing acid with exhaust gas. The method is tested in a factory, and the predicted results are highly identical with actual data. It plays an important guiding role for the adjustment and optimization of process index and exhaust emissions conforming to the standards.
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黄远红,黄清宝.GA-ELM在硫铁矿制酸尾气SO2浓度预测的应用.计算机系统应用,2017,26(10):251-255
HUANG Yuan-Hong,HUANG Qing-Bao.Application of ELM in Prediction of SO2 Concentration of the Tail Gas in Producing Acid with Pyrite.COMPUTER SYSTEMS APPLICATIONS,2017,26(10):251-255