|本期目录/Table of Contents|

[1]曾青云,汪金良,张传福.基于自适应模糊神经网络的铜闪速熔炼渣含Fe/SiO2模型研究[J].有色金属科学与工程,2016,(05预):1-004.
 of Copper Flash Smelting Process Based on ANFIS.Research of the Fe/SiO2 in Slag Model[J].,2016,(05预):1-004.
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基于自适应模糊神经网络的铜闪速熔炼渣含Fe/SiO2模型研究(/HTML)
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《有色金属科学与工程》[ISSN:1674-9669/CN:36-1311/TF]

卷:
期数:
2016年05期预
页码:
1-004
栏目:
出版日期:
2016-10-31

文章信息/Info

Title:
Research of the Fe/SiO2 in Slag Model
作者:
曾青云12汪金良12张传福2
1. 江西理工大学,赣州,341000 2. 中南大学,长沙,410005
Author(s):
of Copper Flash Smelting Process Based on ANFIS
Qingyun Zeng1,2, Jinliang Wang 1,2,Chuanfu Zhang2 1Jiangxi University of Science and Technology, Ganzhou, 341000 2. Central South University, Changsha 410005
关键词:
闪速熔炼模糊控制神经网络仿真
分类号:
-
DOI:
-
文献标志码:
-
摘要:
基于Sugeno型自适应模糊神经网络系统(ANFIS)及利用某闪速炼铜厂生产实践的稳定数据,建立了网络结构为3输入、单输出、隶属度函数个数为[5 3 5]的闪速炼铜过程的渣含Fe/SiO2模型。结果显示其训练数据平均绝对误差为0.0055,相对误差为1.4%;仿真检验数据平均绝对误差为0.028,相对误差为2.9%,表明所建立的模型预测值与生产操作数据基本吻合,该模型对铜熔炼过程的最优化具有参考价值,可以代替现有的静态配料模型用于工业在线计算机控制。

参考文献/References:

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[4] 曾青云,周立,汪金良,刘桦. 基于自适应模糊神经网络的铜闪速熔炼冰铜温度模型研究[J].有色金属(冶炼部分),2007,(2):2-4
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[8] Li Zhen-Quan,Kecman V.,Ichikawa A.Fuzzified Neural Network Based on Fuzzy Number Operation[J],Fuzzy Sets and Systems.2002,130:291—304
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备注/Memo

备注/Memo:
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更新日期/Last Update: 2016-03-29