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Research on SOFMNN in Coal and Gas Outburst Safety Prediction

机译:SOFMNN在煤与瓦斯突出安全预测中的研究。

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摘要

The mechanism of coal and gas outburst is still controversial, many occurrences of accidents have been a serious threat to people's life and property safety. In order to reduce the effect of coal and gas outburst disaster, the prediction of coal and gas outburst situation has a practical significance. Patent describing intelligent algorithms have been successfully applied in the prediction of coal and gas outburst. The self organizing feature mapping neural network is a high efficiency algorithm mechanism. Based on a comparison with the self organizing feature mapping neural network and improved colony clustering method, the accuracy rate of new algorithm is higher than the old method. This research is good for safety engineering development. The experiments performed demonstrate the effectiveness of the algorithm; this method has reference significance for the prediction of coal and gas outburst.
机译:煤与瓦斯突出的机理仍存在争议,许多事故的发生已严重威胁着人们的生命和财产安全。为了减少煤与瓦斯突出灾害的影响,对煤与瓦斯突出情况的预测具有现实意义。描述专利的智能算法已成功应用于煤与瓦斯突出的预测。自组织特征映射神经网络是一种高效的算法机制。在与自组织特征映射神经网络和改进的菌落聚类方法进行比较的基础上,新算法的准确率高于旧方法。这项研究对安全工程的发展很有帮助。实验表明该算法是有效的。该方法对煤与瓦斯突出的预测具有参考意义。

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