由于煤与瓦斯突出发生机理的复杂性,传统预测方法的应用受到很大的限制,而人工神经网络理论以其高度非线性映射的特性为解决这一问题提供了新的途径。以突出预测指标为基础,利用多层反向传播神经网络(BP网络)模型实现对突出危险性的预测。实例分析表明,模型精度很高,可用于工作面煤与瓦斯突出危险性的预测。 Due to the complicated mechanism of coal and gas outburst, the application of traditional prediction methods is greatly limited, and artificial neural network theory provides a new way to solve this problem with its highly nonlinear mapping characteristics. Based on the predication index, the forecasting of the outstanding risk is carried out by using the multilayer backpropagation neural network (BP network) model. The case study shows that the model has high precision and can be used to predict the danger of coal and gas outburst in working face.