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煤矿瓦斯涌出量预测是矿井安全中的一个关键和热点问题。煤矿瓦斯涌出量涉及很多因素,例如日产量、日进度、煤层厚度、煤层间距、煤层深度等,瓦斯涌出量预测是一个非线性问题。径向基神经网络是目前应用非常广泛的一种局部神经网络模型,在函数回归、序列预测中具有很好的应用效果。文中提出了将径向基神经网络用于预测煤矿瓦斯涌出量的想法,并分析了可行性。
Coal mine gas emission prediction is a key and hot topic in mine safety. The gas emission of coal mines involves many factors, such as daily output, daily progress, coal seam thickness, coal seam spacing and coal seam depth. Prediction of gas emission is a nonlinear problem. Radial basis neural network is a very popular local neural network model, which has a good application effect in function regression and sequence prediction. In this paper, the idea of using RBF neural network to predict gas emission from coal mines is proposed and its feasibility is analyzed.