基于BN-ELM的煤矿瓦斯风险预测与可视化研究

Research on Coal Mine Gas Risk Prediction and Visualization based on BN-ELM

煤矿风险预测可以准确掌握煤矿安全生产状况,为决策者提供数据支持。根据煤矿的实时监测数据,以瓦斯风险为例,基于贝叶斯网络与极限学习机(BN-ELM)建立风险预测模型,将预测值与实际值进行比对,并进行可视化表示。结果表明:基于此模型进行预测,可达到较高的准确率,可视化的结果直观地使管理者做出相应的决策与管理。

Coal mine risk prediction can accurately grasp the status of coal mine safety production and provide data support for decision-makers.According to the real-time monitoring data of coal mine,taking gas risk as an example,a risk prediction model is established based on Bayesian network and extreme learning machine(BN-ELM).The predicted value is compared with the actual value and expressed visually.The results show that the prediction based on this model can achieve high accuracy,and the visual results directly enable managers to make corresponding decisions and management.