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运用BP网络分析尿素合成塔CO_2转化率
引用本文:许峰,王煤,邱添,刘正全.运用BP网络分析尿素合成塔CO_2转化率[J].化工设计通讯,2005,31(1):1-3.
作者姓名:许峰  王煤  邱添  刘正全
作者单位:1. 四川大学化工学院,成都,610065
2. 建峰化工总厂化肥分厂,重庆,400002
摘    要:采用BP神经网络模型预测尿素合成塔CO_2 转化率 ,分析了氨碳比和水碳比与转化率之间的关系。详细介绍了建模过程并对隐含层神经元数和迭代次数对网络性能的影响进行了讨论。分析结果表明 :所建模型能准确地对CO_2 转化率进行预测 ,平均相对误差在 1 0 %以内 ;CO_2 转化率随氨碳比的增大而显著增加 ,水碳比的影响则相对较小。

关 键 词:BP神经网络  CO_2转化率  建模  配料比
文章编号:1003-6490(2005)01-0001-03
修稿时间:2004年12月29

CO2 Conversion Rate Analysis of Urea Synthesis Tower By Means of BP Network
XU Feng,WANG Mei,QIU Tian,LIU Zheng-quan.CO2 Conversion Rate Analysis of Urea Synthesis Tower By Means of BP Network[J].Chemical Engineering Design Communications,2005,31(1):1-3.
Authors:XU Feng  WANG Mei  QIU Tian  LIU Zheng-quan
Abstract:This article introduces how to use BP nerve network model to forecast CO 2 comversion rate of urea synthesis tower It also introduces the relationship between ammonia carbon ratio and water carbon ratio and conversion rate It describes the model establishment process and discusses the effect of hidden nerve cell number and iterative times on network performance Analysis result shows that established model can accurately forecast CO 2 conversion rate Average relative error is with in 1 0% CO 2 conversion rate increases greatly along with the increase of ammonia carbon ratio Effect of water carbon ratio is smaller
Keywords:BP nerve network  CO_2 conversion rate  model establishment  proportioning ratio  
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