基于BP神经网络的瓦斯隧道突出预测系统开发研究

摘要

The factors affecting gas outburst in tunnel are so many that it is difficult to build an appropriate non-linear forecast model involving multiple indexes. In this research, a mathematical forecast model of tunnel gas outburst was established using BP neural network, so as to improve accuracy of forecast and enhance operability of forecast method. Meanwhile, by virtue of ASP. NET technology, C # language and SQL Server 2008 database, and by using MATLAB engine technology to call the neural network toolbox under the circumstances of C #. NET, a forecast system of gas outburst was built successfully. And Then the Xiaojialiang Tunnel was taken as an example to test the system actually. It can be seen that the forecasting results accord with the actual situation of tunnel, and this proves that the accurate gas outburst forecast for tunnel can be achieved by using this forecast system.%瓦斯隧道突出影响因素多，难以为其建立合适的多指标非线性预测模型。为了提高突出预测的准确性和增强预测方法的可操作性，采用BP神经网络建立瓦斯隧道突出预测数学模型。借助ASP. NET技术、C#语言和SQL Server 2008数据库，在C#. NET环境下利用Matlab引擎技术调用神经网络工具箱，成功构建了突出预测系统。以肖家梁隧道为例对该系统进行实际检验，预测结果与隧道实际状况达到了较好的一致性，可实现瓦斯隧道突出的准确预测。