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为了准确预测煤与瓦斯突出的危险性,建立有效的煤矿瓦斯预警支持系统,针对煤矿瓦斯灾害的特点,本研究提出了一种新颖的基于粗糙集的瓦斯灾害特征提取算法。该算法首先利用维数化简技术对瓦斯灾害信息矩阵进行优化,并在此基础上,利用信息论中熵的概念和最大熵原理构建瓦斯灾害信息特征提取模型。通过实际应用,证实了粗糙集理论在瓦斯灾害特征提取与瓦斯灾害预测中的有效性和实用性。
In order to accurately predict the danger of coal and gas outburst, an effective coal mine gas warning support system is established. According to the characteristics of coal mine gas disasters, a novel gas disasters feature extraction algorithm based on rough sets is proposed. The algorithm first uses the dimension reduction technique to optimize the gas disaster information matrix, and based on this, uses the concept of entropy and the principle of maximum entropy to construct the gas disaster information feature extraction model. Through practical application, the validity and practicability of rough set theory in gas disaster feature extraction and gas disaster prediction are confirmed.