补偿模糊神经网络在煤矿安全预警中的应用

Application of compensatory fuzzy neural network in coal mine safety early warning

为了实现煤矿安全预警的及时、准确和有效,预防和减少煤矿事故的发生,采用补偿模糊神经网络理论,设计了一种包括"影响因素-综合评价"的二级神经网络结构,其中影响因素级由5个、综合评价级由1个,总共6个子补偿模糊神经网络构成。该结构有利于对影响安全问题的原因进行深入分析,评价更客观。通过实际应用,验证了该模型的实用性和有效性。

To sound a safety early warning timely,accurately and effectively in coal mines so as to decrease and prevent coal mine accidents,compensatory fuzzy neural network was based on to design a two-level neural network structure of ＂influence factors comprehensive evaluation ＂.This structure consists of 6 sub-compensatory fuzzy neural networks of which five are influence factors and one comprehensive evaluation.It i.s good for further analyses of causes for safety and more objective evaluation. The application proves the model＇s practicability and validity.