Predicting Pulverized Coal Plasma Ignition Performance by BP Neural Network

DOI

10.2991/masta-19.2019.3How to use a DOI?

Keywords

BP Neural Network, Plasma Ignition, Prediction model, Pulverized coal streams

Abstract

To make sure the major factors and their influence for pulverized coal plasma ignition(PCPI), the way predicting the PCPI was investigated in this paper. The back propagation(BP) neural network was used to established a prediction model which can study by itself for PCPI. Then the sample database was set up by simulating the PCPI in kinds of conditions. After that, the prediction model was trained by sample database to improve the prediction level. At last, the prediction model was used to predict the PCPI in new conditions and the prediction error is under 0.004. The research show that the BP neural network can predict the PCPI correctly. In this paper, the BP neural network was applied to predict the PCPI innovatively, and the prediction efficiency increase highly and the prediction accurancy does not deline.

Copyright

© 2019, 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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TY  - CONF
AU  - Lei Shi
AU  - Yi Zhang
AU  - Yu-bin Men
AU  - Ji Cheng
PY  - 2019/07
DA  - 2019/07
TI  - Predicting Pulverized Coal Plasma Ignition Performance by BP Neural Network
BT  - Proceedings of the 2019 International Conference on Modeling, Analysis, Simulation Technologies and Applications (MASTA 2019)
PB  - Atlantis Press
SP  - 15
EP  - 19
SN  - 1951-6851
UR  - https://doi.org/10.2991/masta-19.2019.3
DO  - 10.2991/masta-19.2019.3
ID  - Shi2019/07
ER  -