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

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

By:  and    
Open Access
|Oct 2019

Figures & Tables

Figure 1.

Flow chart of control mode

Table I.

SAMPLE

NO.The temperature of exhaust gas (°C)The temperature of inlet (°C)The pressure of inlet (Pa)The temperature of the second air (°C)The temperature of product (°C)Activity (ml)Product state
12801009-57.78536171360Over-burn
ed
22861014-23.64625143351Over-burn
ed
3273983-25.5463095335under-bur
ned
……………………
116270949-39.46578155329under-bur
ned
1172619547.42571134353under-bur
ned
1182821002-51.04630127365Over-burn
ed
119267967-20.32547109344under-burned
1202821006-55.68628152357Over-burned
……………………
159286996-12.5627141354under-burned
160274949-12.01597112341under-burned
Figure 2.

The contrast of product quality before and after used the system

Language: English
Page range: 83 - 86
Published on: Oct 14, 2019
Published by: Xi’an Technological University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2019 Lingli Zhu, Tingzhong Wang, published by Xi’an Technological University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.