基于ART-2人工神经网络的煤矿安全风险评价

Coal mine safety risk assessment based on ART-2 neural network

旨在为煤矿安全风险预控管理提供一种适用的风险评价模型或方法。研究过程中,介绍了人工神经网络自适应共振理论的ART-2算法;在安全系统工程理论及相关研究基础上,结合调研分析建立了风险评价指标体系;选取山西9家煤矿作为研究样本进行实证研究。该算法仿真识别结果与煤矿实际安全风险情况一致性程度达到77.78%,表明针对煤矿安全风险预控管理过程中的安全风险评价,ART-2神经网络具有较好的适用性。

In order to find an applicative risk assessment model or method for coal mine safety risk pre-controlling management, the ART-2 artificial neural network algorithm was introduced, the safety system management theory was taken as foundation to establish a risk evaluation index system, and the security risk evaluation index datas of 9 coal mines were choosen as the research samples for simulation study. In the simulation results of ART-2 algorithm, 7 of the 9 coals were consistent with the actual safety risk situation of coal mines. It showed that the ART-2 neural network algorithm is an applicative method for coal mine risk assessment in the process of safety risk pre-controlling management.