Studied on Indicator Gases of Coal Based on BP Neural Network Forecasting System

Abstract:

In order to forecast coal spontaneous combustion, take advantage of BP neural network. The date is recorded from one coal mine of Donghuantuo. The input of the neural network is the concentration of CO, CO₂ and CH₄ in different temperature and use CH₄-to-CO, O₂-to-CO₂ ratio. In this way, the influence of the wind will be little. After trained, the network can show 0 or 1 which represent fire or not. After trained 43 times, the error is lower than 0.000 1. It proves that BP neural network can deal with the date of coal mine. What’s more, BP neural network has huge advantages.

• Periodical: Applied Mechanics and Materials (Volume 685)
• Pages: 259-262
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.685.259
• Online since: October 2014
• Authors: Bing Bian*, Zhi Jian Liu, Wei Zhang
• Keywords: Beam Tube Monitoring System, BP Neural Network (BPNN), Concentration of the Indicator Gases, Fire Forecast, Mining Safety

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