%0 Journal Article
%T Research on endpoint prediction model of converting furnace<br>铜转炉吹炼终点预报模型研究*
%A SUN Xin-hong
%A XIE Yong-fang
%A GUI Wei-hua
%A SONG Hai-ying
%A <br>孙鑫红
%A 谢永芳
%A 桂卫华
%A 宋海鹰
%J 计算机应用研究
%D 2007
%I 
%X The endpoint prediction is one of the most important processes of converting furnace. It influences the benefit of the produce directly. The process of converting furnace is completely complex and coupled. To this question, principal component analysis (PCA) method was used to reorganize the factors. On this basis, the genetic algorithm (GA) was introduced by combining Elman neural network to predict the endpoint of converting furnace. The model was set up using MATLAB software. The simulation results show that the model possesses higher precision and practicability.
%K 铜转炉
%K 主元分析法
%K 遗传算法
%K Elman神经网络
%K 转炉吹炼
%K 终点预报模型
%K 研究
%K furnace
%K prediction
%K model
%K 精度
%K 仿真结果
%K 泛化能力
%K 自学习
%K 网络模型
%K 神经
%K Elman
%K 基于遗传算法
%K 重组
%K 影响因素
%K 主元分析法
%K 利用
%K 问题
%K 吹炼终点
%K 预测
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=C793235A4E87B8F6C0DCAFC37ADC795E&yid=A732AF04DDA03BB3&vid=B91E8C6D6FE990DB&iid=708DD6B15D2464E8&sid=BFE7933E5EEA150D&eid=95D537AC89B28832&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=11