【作者】 张攀；

【导师】 刘剑；

【作者基本信息】 辽宁工程技术大学 ， 安全技术及工程， 2004， 硕士

【摘要】 标准风阻值和标准摩擦阻力系数值作为矿井通风技术管理的基本资料对矿井通风管理具有重要意义。本文从影响摩擦阻力系数的直接原因出发来进行参数确定而避免了实际测量的繁重工作，归纳出了不同支护形式巷道的数学计算公式。另外，运用改进的BP神经网络模型对巷道摩擦阻力系数进行了模式识别，合理地选择适当的参数作为神经网络的输入参数，运用改进贝叶斯正则化方法对网络进行训练从而达到方便的确定摩擦阻力系数的目的。该方法的主要优点有:网络结构简单,收敛速度快,预测精度高。并通过实测和应用验证了这两种数学模型的正确性，为其在工程实践中的广泛应用奠定了理论基础更多还原

【Abstract】 The standard value of ventilation resistance and coefficient of frictional resistance is very significant to the ventilation management of the mine as the basic data. It is introduced that confirming coefficient of frictional resistance by the immediate causes avoids heavy work of measurement, and summing up the computing formula of mathematics to those different roadways of bracket. In addition, applying an improved BP artificial neural network on pattern recognition calculates the coefficient value of frictional resistance. We can select rationally relevant parameters as input value of these models, and apply the Bayesian Regularization to them. The main advantages of them include simple structure, efficient convergence, precise forecasting, etc. The validity of their mathematical models is tested by their actual measure and application, and the mathematical models provide the theoretical foundation for their application in engineering practice.更多还原