The Research of back propagation neural network based on genetic algorithm in the gas concentration prediction

DOI

10.2991/icismme-15.2015.174How to use a DOI?

Keywords

gas concentration; Genetic Algorithm; BP neural network; prediction model.

Abstract

The prediction of gas concentration is an extremely complicated nonlinear dynamic system which cannot fully use precise mathematical language to describe. Only using BP neural network algorithm is easy to converge to the local minimal point in the gas concentration prediction, so this paper presents the idea of GA-BP of neural network, which set up the GA - BP neural network model by optimizing the weights and threshold of BP neural network and its application in coal gas concentration prediction. This method combining genetic algorithm and neural network, and use genetic algorithm to optimize neural network to the initial value, so that the BP network can convergence to the optimal solution fast and can achieve higher precision in a shorter period, and the rate of convergence, accuracy and stability is superior to the BP network model, Thus verified the rationality and effectiveness of the GA - BP neural network.

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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TY  - CONF
AU  - Dapeng Liu
AU  - Fengying Ma
PY  - 2015/07
DA  - 2015/07
TI  - The Research of back propagation neural network based on genetic algorithm in the gas concentration prediction
BT  - Proceedings of the First International Conference on Information Sciences, Machinery, Materials and Energy
PB  - Atlantis Press
SP  - 831
EP  - 834
SN  - 1951-6851
UR  - https://doi.org/10.2991/icismme-15.2015.174
DO  - 10.2991/icismme-15.2015.174
ID  - Liu2015/07
ER  -