[1]宋蕾,陈德运,姚玉梅,等.Elman神经网络在ECT系统流型辨识中的应用[J].哈尔滨理工大学学报,2014,(05):103-108.
 SONG Lei CHEN De-yun YAO Yu-mei LlJia-nan WANG Li-Li.Application of Elman Neural Network in Pattern Identification for Electrical Capacitance Tomography[J].哈尔滨理工大学学报,2014,(05):103-108.
点击复制

Elman神经网络在ECT系统流型辨识中的应用
()
分享到:

《哈尔滨理工大学学报》[ISSN:1007-2683/CN:23-1404/N]

卷:
期数:
2014年05期
页码:
103-108
栏目:
计算机与控制工程
出版日期:
2014-10-25

文章信息/Info

Title:
Application of Elman Neural Network in Pattern Identification for Electrical Capacitance Tomography
文章编号:
1007一2683(2014)05一0103一06
作者:
宋蕾陈德运姚玉梅林甲楠王莉莉
(哈尔滨理工大学计算机科学与技术学院,黑龙江哈尔滨 150080)
Author(s):
SONG Lei CHEN De-yun YAO Yu-mei Ll、Jia-nan WANG Li-Li
(School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080,China)
关键词:
电容层析成像流型辨识Elman神经网络收敛速度
Keywords:
electrical capacitance tomographyflow regime identificationElman neural networkconvergence speed
分类号:
TP216
文献标志码:
A
摘要:
针对电容层析成像系统ECT ( electrical capacitance tomography)流型辨识问题,在对ECT系统工作原理和流型的辨识方法分析的基础上,提出了一种基于Elman神经网络的ECT系统流型辨识方法,该方法通过对ECT系统采集的电容值特征值提取与处理,将提取的特征值作为E1-man神经网络的输入进行训练,经训练后达到流型辨识的目的.经仿真实验验证,与传统的BP神经网络相比,该方法具有结构简单,收敛速度快,不会因阶次未知而出现网络结构膨胀的问题,为ECT系统流型辨识的提供一种的有效方法.
Abstract:
To solve the problem of electrical capacitance tomography(ECT ) system of flow regime identification,this paper presents a new method based on Elman neural network for ECT system of flow pattern identification,which is on the basis of the work principle of ECT system and the method of flow pattern identification. This method uses part of capacitance to extract its feature,and uses the extracted data to train the Elman neural network to achieve the aim of recognize the type of the flow.After simulation,the result shows that this method is better than BP neural network. This method has a simple structure and a fast convergence speed,at the same time;it does not have the network expansion problem of the unknown order. It is an effective method for ECT system of flow pattern identification.

相似文献/References:

[1]陈德运,李乐天,胡海涛,等.基于迭代Tikhonov正则化的电容层析成像图像重建[J].哈尔滨理工大学学报,2009,(02):1.
 CHEN De-yun,LI Le-tian,HU Hai-tao.Image Reconstruction Algorithm Based on Iterated Tikhonov Regularization for Electrical Capacitance Tomography[J].哈尔滨理工大学学报,2009,(05):1.
[2]郭虹,李岩,张礼勇,等.12电极相干电容层析成像检测系统[J].哈尔滨理工大学学报,2009,(05):31.
 GUO Hong,LI Yan,ZHANG Li-yong.12-electrodes Electrical Capacitance Tomography Detection System Based on Relevant Technology[J].哈尔滨理工大学学报,2009,(05):31.
[3]陈宇,孙帆,张健,等.三项共轭梯度的电容层析成像图像重建算法[J].哈尔滨理工大学学报,2009,(06):42.
 CHEN Yu,SUN Fan,ZHANG Jian.A Novel Three Conjugate Gradient Image Reconstruction Algorithm for Electrical Capacitance Tomography System[J].哈尔滨理工大学学报,2009,(05):42.
[4]陈宇,孙帆,张健,等.基于自适应权重粒子群的电容层析成像边界灰度补偿算法[J].哈尔滨理工大学学报,2010,(03):44.
 CHEN Yu,SUN Fan,ZHANG Jian.A Novel Gray Boundary Compensation Algorithm for Electrical Capacitance Tomography System Based on Adaptive Particle Swarm Weight[J].哈尔滨理工大学学报,2010,(05):44.
[5]李岩,朱艳丹,袁小花,等.基于ANSYS电容层析成像结构参数分析与优化[J].哈尔滨理工大学学报,2012,(01):54.
 LI Yan,ZHU Yan-dan,YUAN Xiao-hua,et al.Analysis and Optimization of Structural Parameters Based on ANSYS in ECT[J].哈尔滨理工大学学报,2012,(05):54.
[6]陈宇,许莉薇,江露,等.成像流型辨识算法[J].哈尔滨理工大学学报,2014,(04):111.
 CHEN Yu,XU Li-wei,JIANG Lu,et al.[J].哈尔滨理工大学学报,2014,(05):111.
[7]姚玉梅,陈德运,林甲楠,等.一种多小波电容层析成像图像融合方法[J].哈尔滨理工大学学报,2014,(05):88.
 YAO Yu-mei,CHEDe-yun,LlJia-nan,et al.Image Fusion Method Based on Multi Wavelet Transform for Electrical Capacitance Tomography[J].哈尔滨理工大学学报,2014,(05):88.
[8]林甲楠,陈德运,姚玉梅,等.一种分解型Quasi-Newton电容层析成像图像重建算法[J].哈尔滨理工大学学报,2014,(06):44.
 LlN Jia-nan,CHEN De-yun,YAO Yu-mei,et al.A Novel Factorized Quasi一Newton Image Reconstruction Algorithm for Electrical Capacitance Tomography[J].哈尔滨理工大学学报,2014,(05):44.
[9]陈宇,许莉薇,黄仲洋,等.SADE-ELM电容层析成像流型辨识算法[J].哈尔滨理工大学学报,2014,(06):32.
 CHEN Yu,XU Li-wei,HUANG Zhong-yang,et al.A Self一adaptive Different Evolution Extreme Learning Algorithm for Electrical Capacitance Tomography System[J].哈尔滨理工大学学报,2014,(05):32.
[10]李岩,杜永斌,宋海丰,等.ECT系统轮换对称svM图像重建改进算法[J].哈尔滨理工大学学报,2015,(03):40.
 LI Yan .DU Yong-bin .SONG Hai-fence.MAN Zhi-qian}.REN Xiang-h ua.Improved Method of Electrical Capacitance Tomography Based onSVM Algorithm of Cyclic Symmetrical Partition[J].哈尔滨理工大学学报,2015,(05):40.

备注/Memo

备注/Memo:
国家白然科学基金( 60572153,60972127) ;高等学校博十学科点专项科研基金(200802140001);黑龙江省自然科学基金(QC2012CO59);黑龙江省教育厅计划项目(11541040,12511097).
更新日期/Last Update: 2015-05-12