| BP神经网络在液相传质系数中的应用 |
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| 引用本文： | 王晶瑞,王承学. BP神经网络在液相传质系数中的应用[J]. 吉林工学院学报, 2006, 27(4): 283-285 |
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| 作者姓名： | 王晶瑞 王承学 |
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| 作者单位： | 长春工业大学化学工程学院 吉林长春130012 |
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| 基金项目： | 吉林省科技厅科学基金资助项目(19980564) |
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| 摘 要： | 根据BP(Back-Propagation)神经网络原理,以气、液表观流率为输入变量,液相传质系数为输出变量,建立神经网络模型,并利用改进的LM(Levenberg-Marquardt)算法对网络进行了训练和优化。结果表明,BP神经网络能够较好地预测滴流状态下H2O吸收CO2液相传质系数。
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| 关 键 词： | 液相传质系数 BP神经网络 |
| 文章编号： | 1006-2939（2006）04-0283-03 |
| 收稿时间： | 2006-06-18 |
| 修稿时间： | 2006-06-18 |
Application of BP neural network in liquid-side mass transfer coefficients |
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| WANG Jing-rui,WANG Cheng-xue. Application of BP neural network in liquid-side mass transfer coefficients[J]. Journal of Jilin Institute of Technology, 2006, 27(4): 283-285 |
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| Authors: | WANG Jing-rui WANG Cheng-xue |
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| Affiliation: | College of Chemical Engineering, Changchun University of Technology, Changchun 130012, China |
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| Abstract: | Based on the principle of BP(Back-Propagation)neural network,a neural network model was established,with gas and liquid velocities as inputs,liquid-side mass transfer coefficient as(output).By using Levenberg-Marquardt(LM)algorithm,the net was trained and optimized.Results showed that BP neural(network) could predict liquid-side mass transfer coefficient for CO_2 absorbed by H_2O in the trickled condition. |
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| Keywords: | liquid-side mass transfer coefficient BP neural network. |
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