摘要
瓦斯浓度在很大程度上决定了煤矿井下发生爆炸的可能性,而原有灰色模型预测方法精度不是很高,但是所需的数据较少,而BP神经网络有高度的非线性计算、自学习和自组织能力。本文结合了灰色系统与BP神经网络各自的优点进行预测,使预测结果更加精确,可靠性得到很大的提高。
Gas concentration to a large extent determines the possibility of coal mine explosion,while the original gray model method is not very high precision,but required less data,while the BP neural network is highly non-linear calculation,self-learning and self-organization capability.In this paper,the combination of the gray system and BP neural network ＇s merits to predict,so that more accurate prediction,reliability is greatly improved.
出处
《微计算机信息》
2011年第5期42-43,151,共3页
Control & Automation
