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Delay Time Identification and Dynamic Characteristics Study on ANN Soft Sensor
Jinan, China October 16-October 18
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ISDA.2006.131Sixth International Conference on Int ...
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Dianlin Du, Chongguang Wu, Xionglin Luo, Xin Zuo, "Delay Time Identification and Dynamic Characteristics Study on ANN Soft Sensor," Intelligent Systems Design and Applications, International Conference on, vol. 1, pp. 42-45, Sixth International Conference on Intelligent Systems Design and Applications (ISDA'06) Volume 1, 2006.
 
 
BibTex
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@article{ 10.1109/ISDA.2006.131,
author = {Dianlin Du and Chongguang Wu and Xionglin Luo and Xin Zuo},
title = {Delay Time Identification and Dynamic Characteristics Study on ANN Soft Sensor},
journal ={Intelligent Systems Design and Applications, International Conference on},
volume = {1},
year = {2006},
isbn = {0-7695-2528-8},
pages = {42-45},
doi = {http://doi.ieeecomputersociety.org/10.1109/ISDA.2006.131},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Intelligent Systems Design and Applications, International Conference on
TI - Delay Time Identification and Dynamic Characteristics Study on ANN Soft Sensor
SN - 0-7695-2528-8
SP42
EP45
A1 - Dianlin Du,
A1 - Chongguang Wu,
A1 - Xionglin Luo,
A1 - Xin Zuo,
PY - 2006
KW - artificial neural network
KW - soft sensor
KW - delay time
KW - dynamic system
VL - 1
JA - Intelligent Systems Design and Applications, International Conference on
ER -
 
Dianlin Du, Beijing University of Chemical Technology, China
Chongguang Wu, Beijing University of Chemical Technology, China
Xionglin Luo, ChinaUniversity of Petroleum, China
Xin Zuo, ChinaUniversity of Petroleum, China
sensor software based on ANN(Artificial Neural Network) using BP or RBF was developed to estimate unmeasured variables such as product quality online. Some important topics including how to determine the delay time, how to simulate the dynamic system were discussed and solved. We applied a 3 layers BP network to identify the delay time of nonlinear system, feedback output variables to input layer, and weight all the input variables to describe dynamic characteristics of the system. This makes the ANN soft sensor reflect truly both the static and dynamic characteristics of the system and provide more adaptability.
Index Terms:
artificial neural network, soft sensor, delay time, dynamic system
Citation:
Dianlin Du, Chongguang Wu, Xionglin Luo, Xin Zuo, "Delay Time Identification and Dynamic Characteristics Study on ANN Soft Sensor," isda, vol. 1, pp.42-45, Sixth International Conference on Intelligent Systems Design and Applications (ISDA'06) Volume 1, 2006
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