| 基于BP神经网络的MCM-22分子筛催化性能预测模型研究 |
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| 引用本文： | 唐艳,李建伟,孙晓岩,李英霞,陈标华. 基于BP神经网络的MCM-22分子筛催化性能预测模型研究[J]. 北京化工大学学报(自然科学版), 2010, 37(1): 13-18. DOI: 10.3969/j.issn.1671-4628.2010.01.004 |
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| 作者姓名： | 唐艳 李建伟 孙晓岩 李英霞 陈标华 |
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| 作者单位： | 北京化工大学 化工资源有效利用国家重点实验室， 北京 100029 |
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| 基金项目： | 国家自然科学基金(20576012) |
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| 摘 要： | 基于人工神经网络建模方法,建立了MCM-22分子筛催化剂在苯与丙烯液相烷基化过程中性能预测的BP神经网络模型,该模型关联了催化剂本征性能、工艺条件和反应产物分布之间的相互关系。对不同成型条件下得到的16种结构性能各异的MCM-22分子筛催化剂性能进行实验评价,将所获得的数据用于模型训练和预测结果检验。结果表明,所建立的模型对MCM-22分子筛催化性能具有较高的预测精度,预测平均相对误差为4.21%。因此,将BP神经网络作为MCM-22分子筛催化剂的性能预测和苯与丙烯液相烷基化过程的定量描述模型,是适宜和可靠的。
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| 关 键 词： | BP神经网络 MCM-22分子筛 催化性能 预测 烷基化 |
| 收稿时间： | 2009-03-17 |
Performance prediction model for a MCM-22 zeolite catalyst based on a back-propagation neural network |
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| TANG Yan,LI JianWei,SUN XiaoYan,LI YingXia,CHEN BiaoHua. Performance prediction model for a MCM-22 zeolite catalyst based on a back-propagation neural network[J]. Journal of Beijing University of Chemical Technology, 2010, 37(1): 13-18. DOI: 10.3969/j.issn.1671-4628.2010.01.004 |
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| Authors: | TANG Yan LI JianWei SUN XiaoYan LI YingXia CHEN BiaoHua |
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| Affiliation: | State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Beijing 100029, China |
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| Abstract: | Based on the artificial neural networks(ANN) modeling method,a back-propagation(BP) neural networks model was developed for the performance prediction of an MCM-22 zeolite catalyst in the liquid alkylation of benzene with propylene.The intrinsic performance of the MCM-22 zeolite,the process conditions,and the product distribution were included in the model.By means of the extrusion molding method,16 kinds of MCM-22 zeolite catalysts with different textural properties were prepared,and their catalytic perfor... |
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| Keywords: | back-propagation neural networks MCM-22 zeolite catalytic performance prediction alkylation |
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