Proceedings of the 8th International Conference on Management and Computer Science (ICMCS 2018)

Application of Improved BP Neural Network in Hybrid Control Model of Lime Quality

Authors
Lingli Zhu, Tingzhong Wang
Corresponding Author
Lingli Zhu
Available Online October 2018.
DOI
10.2991/icmcs-18.2018.17How to use a DOI?
Keywords
Improved Neural Network; Lime; Expert System; BP; Hybrid Control
Abstract

In this paper, a method of combining neural network with expert system is proposed, which can realize the control model of real time feedback and control parameters. The model is based on the parameters of production condition, and the current lime quality is predicted. Through the quality of lime and control parameters, using association rule base of expert system, reasoning that lime control parameter adjustment, timely feedback to the lime production control system, to achieve the purpose of real-time control of the quality of lime. The paper presents application of improved BP neural network in hybrid control model of lime quality.

Copyright
© 2018, 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 8th International Conference on Management and Computer Science (ICMCS 2018)
Series
Advances in Computer Science Research
Publication Date
October 2018
ISBN
10.2991/icmcs-18.2018.17
ISSN
2352-538X
DOI
10.2991/icmcs-18.2018.17How to use a DOI?
Copyright
© 2018, 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  - Lingli Zhu
AU  - Tingzhong Wang
PY  - 2018/10
DA  - 2018/10
TI  - Application of Improved BP Neural Network in Hybrid Control Model of Lime Quality
BT  - Proceedings of the 8th International Conference on Management and Computer Science (ICMCS 2018)
PB  - Atlantis Press
SP  - 89
EP  - 93
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmcs-18.2018.17
DO  - 10.2991/icmcs-18.2018.17
ID  - Zhu2018/10
ER  -