Effect analysis of coal seam water infusion based on genetic algorithm-BP neural network

LIU Jinwei; XIE Xionggang; FANG Jing

doi:10.13272/j.issn.1671-251x.2016.01.014

Volume 42 Issue 1

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LIU Jinwei, XIE Xionggang, FANG Jing. Effect analysis of coal seam water infusion based on genetic algorithm-BP neural network[J]. Industry and Mine Automation, 2016, 42(1): 48-51. doi: 10.13272/j.issn.1671-251x.2016.01.014

Citation:

LIU Jinwei, XIE Xionggang, FANG Jing. Effect analysis of coal seam water infusion based on genetic algorithm-BP neural network[J]. Industry and Mine Automation, 2016, 42(1): 48-51. doi: 10.13272/j.issn.1671-251x.2016.01.014

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Effect analysis of coal seam water infusion based on genetic algorithm-BP neural network

doi: 10.13272/j.issn.1671-251x.2016.01.014

LIU Jinwei^{1, 2},
XIE Xionggang^{1, 2, 3},
FANG Jing^{1, 2}

1.
Mining College, Guizhou University, Guiyang 550025, China
2.
Engineering Center for Safe Mining Technology under Complex Geologic Conditions, Guizhou University, Guiyang 550025, China
3.
Guizhou Eng

Publish Date: 2016-01-10

Abstract

Abstract

In order to improve prediction accuracy of coal seam water infusion effect by using BP neural network, genetic algorithm was used to optimize weight value and threshold value of BP neural network. Genetic algorithm-BP neural network model was built and used to predict wetting radius of coal seam water infusion. The Matlab simulation result shows that the genetic algorithm-BP neural network model has more accurate prediction result than BP neural network model, average relative error of the genetic algorithm-BP neural network model is reduced by 40.29%, training steps are reduced by 1 665 steps, convergence speed is fast and stability is good. Key words:
- coal seam water infusion,
- BP neural network,
- genetic algorithm-BP neural network model,
- wetting radius