基于BP神经网络的非煤地下矿山安全评价模型

针对非煤地下矿山安全评价的复杂性和非线性特性,BP神经网络对非线性动态系统较强的适应性,提出并建立了一种基于BP神经网络的非煤地下矿山安全评价模型。为提高该模型的可靠性,结合非煤地下矿山生产工艺特点,提出了一套便于统计和赋值的安全评价指标体系;确定了BP神经网络结构和评价结果表征方法;为提高BP神经网络算法的收敛速度和稳定性,对标准BP算法进行有效改进;通过实例运算验证了该模型的可行性。基于BP神经网络的安全评价模型为评价非煤地下矿山安全管理现状及水平提供了可操作的方法,为矿山有关部门提供了科学安全管理的依据。

Safety Assessment Model of Underground Non-coal Mine Based on BP Neural Network

A kind of underground non-coal mine safety assessment model based on BP neural network is raised and constructed in the light of the complexity and nonlinear characteristic of underground non-coal mine safety assessment,as well as the strong adaptability of BP neural network to nonlinear dynamic system. In order to improve the reliability of this assessment model,an easily calculated and valued safety assessment index system is put forward in accordance with the production features of underground non-coal mine; the network structure and the method expressing the assessment results are determined; and the standard BP calculation method is effectively improved to enhance the convergence speed and stability of BP neural network calculation. Finally the feasibility of the model is verified through some cases. This assessment model based on BP neual network provides advisable methods for the assessment of underground non-coal mine safety management status,and basis for scientific and safe management of the relative departments.