Prediction of Coal and Gas Outburst by BP Neural Network

Abstract:

Accidents of coal mine have happened frequently in china and coal and gas outburst is a common and serious disaster. Outbursts are often accompanied by the release of gas and lead to gas suffocation and explosions. In this paper, we use BP neural network to predict outbursts. We selected mining depth, gas pressure, initial speed of gas emission, firmness coefficient and geological extent as the main factors of outbursts. By analyzing and comparing we established a prediction model which has 5 neurons in input layer, 14 in middle layer, 1 in output layer and the model is established based on Matlab7.8.0. Experimental results show that simulated curves have the same trend with actual curve, so the method is feasible.

• Periodical: Applied Mechanics and Materials (Volume 539)
• Pages: 664-668
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.539.664
• Online since: July 2014
• Authors: Guang Zhang*, Zhi Jun Liu, Yi Wen Yang, Chang Chuan Chen
• Keywords: BP Neural Network (BPNN), CoAl, Gas Outburst, Prediction Model

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