基于信念网络的岩爆倾向性预测模型研究

为了在岩爆预测精确度和工程实用性之间寻找平衡点，提出基于信念网络的岩爆等级预测模型，综合考虑岩爆的发生机理和目前已有的判别依据，选取最大切向应力与岩石单轴抗压强度比值等因素作为评价指标。在专家论证的样本数据集的基础上，采用梯度下降法对输入不完备信息进行预测优化；应用NETICA软件对已有的样本信息进行统计训练后获得节点间的概率分布，分析了各判据节点与目标节点的敏感度。利用该预测模型对工程实例进行分析预测，验证了模型的可行性，为岩爆等级预测提供一种新的方法和途径。

Study on Prediction Model of Rockburst Proneness Based on Belief Network

In order to balance the prediction accuracy of rockburst and engineering practicability, a prediction model of rockburst grade based on belief network was proposed. The mechanism of rockburst and the existing discrimination criterion were considered comprehensively, factors such as the maximum tangential stress and the ratio of uniaxial compressive strength of rock were chosen as the evaluation indexes. Based on the sample data set of expert argumentation, the input incomplete information was forecasted and optimized by the gradient descent method. By using the NETICA software, the existing sample information was statistically trained, and the probability distribution among nodes was obtained, the sensitivity of each criterion node to the target node was analyzed. Using the prediction model to analyze and forecast engineering project, which verifies the feasibility of the model providing a new method for rockburst grade prediction.