基于自组织神经网络的煤矿安全预警系统

Coal safety early-warning system base on self-organization neural networks

结合煤矿安全生产的具体要求,将自组织神经网络原理运用于煤矿安全预警问题中,建立了多指标综合评价的安全预警系统网络模型,并以实测数据为例对所建模型进行了训练和检验,研究结果表明,该网络性能良好、预测精度高且简便易行,是安全综合评价的一种有效方法。

With the demand of coal safety production, using the principle of self-organization neural networks in coal safety early-warning system, the model of multi-index safety quality synthesis evaluation was established. The model is trained and tested by the examples of real sample data. The results show that self-organization neural networks have an excellent network performance, high prediction accuracy and are easy to use. As a result, it is an effective safety synthesis evaluation method.