基于模糊聚类分析和模糊模式识别的煤与瓦斯突出预测

Regional forecast of coal and gas burst based on fuzzy cluster analysis and fuzzy pattern recognition

  • 摘要: 煤与瓦斯突出发生的内在机理复杂,突出影响因素与突出事件之间的相关规律具不精确性和模糊性,使得基于经验的传统预测方法和基于数学建模的统计预测方法的应用受到很大限制。提出了采用模糊聚类分析与模糊模式识别方法相结合的煤与瓦斯突出区域预测方法。首先采用模糊聚类分析对煤与瓦斯突出的样本集合进行分类,建立不同程度的模糊模式,然后对待预测样本进行模糊模式识别,以此来预测待测样本的煤与瓦斯突出危险程度。实例验证表明,本法预测可靠。

     

    Abstract: For complex mechanics of coal and gas outburst,the uncertainty or fuzziness between outburst-factors and outburst-hazard,makes predicting methods both based on experiences and on math-models be limited.A new method in combining the fuzzy cluster analysis and fuzzy pattern recognition is presented to forecast coal and gas burst.Firstly,the simple integration is classified for the coal and gas outburst by adopting clustering analysis method.The fuzzy model is set up for different outburst degree.Afterwards,the danger degree of the undetermined forecasting sample is predicted by applying fuzzy pattern recognition.The accuracy of forecast is improved.Through actual validation,the reliability of the prediction is tested and verified.

     

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