粒子群神经网络在煤与瓦斯突出预测中的应用

煤与瓦斯突出是危害煤矿安全生产的主要因素,因此做好突出强度的预测具有重要的意义。将煤与瓦斯突出的综合影响因素作为特征向量,构建了基于粒子群优化的BP神经网络煤与瓦斯突出强度预测模型。实验结果表明,煤与瓦斯突出强度的预测值与实际值吻合度较好,该方法可有效地提高预测准确度,对实际生产具有一定的指导作用。

Coal and gas outburst is the main factor of the coalmine safety harm, so do the outburst prediction has important sense. Using the influencing factors of coal and gas outburst as feature vectors, establishes coal and gas outburst prediction model by BP neural network based on particle swarm optimization. The experimental results show that the prediction was identical with observed data, this method can effectively improve the prediction accuracy, has a guiding role in the actual production.