Proceedings of the 2015 International conference on Applied Science and Engineering Innovation

Crude Oil Measurement Model Based on Artificial Neural Networks

Authors
Bo Chen, Xiaoqing Xue, Ting Liu
Corresponding Author
Bo Chen
Available Online May 2015.
DOI
10.2991/asei-15.2015.428How to use a DOI?
Keywords
neural network, moisture content of crude oil, error compensation, back propagation
Abstract

ANN technology is being widely used in many fields, Based on the analysis of artificial neural network, a method using multi-sensor in an improved artificial neural network is put forward for the error compensation and control of crude oil measurement model, experimental data are used to verify the result.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2015 International conference on Applied Science and Engineering Innovation
Series
Advances in Engineering Research
Publication Date
May 2015
ISBN
978-94-62520-94-3
ISSN
2352-5401
DOI
10.2991/asei-15.2015.428How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Bo Chen
AU  - Xiaoqing Xue
AU  - Ting Liu
PY  - 2015/05
DA  - 2015/05
TI  - Crude Oil Measurement Model Based on Artificial Neural Networks
BT  - Proceedings of the 2015 International conference on Applied Science and Engineering Innovation
PB  - Atlantis Press
SP  - 2179
EP  - 2182
SN  - 2352-5401
UR  - https://doi.org/10.2991/asei-15.2015.428
DO  - 10.2991/asei-15.2015.428
ID  - Chen2015/05
ER  -