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首页> 外文会议>2007采矿科学与安全技术国际学术会议 >Study on Fuzzy Pattern Recognition for Regional Forecast of Coal and Gas Outburst
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Study on Fuzzy Pattern Recognition for Regional Forecast of Coal and Gas Outburst

机译：煤与瓦斯突出区域预测的模糊模式识别研究。

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For reasons of the complex of coal and gas outburst, the uncertainty or fuzziness between outburst-factors and outburst- hazard, makes predicting methods both based on experiences and based on math-models be helpless. Recurring to well-rounded fuzzy theory and technology can realize exact expression and manage between imprecise information and imprecise relation on outburst prediction. Advanced a new method in combining the fuzzy cluster analysis and fuzzy pattern recognition 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. With the fuzzy cluster analysis and fuzzy pattern recognition to forecast regionally coal and gas burst which can overcome the indeterminateness and change qualitative forecast to quantitave. The accuracy of forecast is improved. Through actual validation, the reliability of the prediction is tested and verified.
机译：由于煤与瓦斯突出的复杂性，突出因素与突出危险之间的不确定性或模糊性使得基于经验和基于数学模型的预测方法变得无能为力。运用完备的模糊理论和技术，可以实现精确的表达，并在不精确的信息和不精确的关系之间进行突发预测。提出了一种将模糊聚类分析与模糊模式识别相结合的预测煤与瓦斯爆炸的新方法。首先，采用聚类分析方法对煤与瓦斯突出进行简单积分分类。针对不同的突出程度建立了模糊模型。然后，通过应用模糊模式识别来预测不确定的预测样本的危险程度。通过模糊聚类分析和模糊模式识别对煤与瓦斯爆发进行区域预测，可以克服不确定性，将定性预测改为定量。提高了预测的准确性。通过实际验证，对预测的可靠性进行了测试和验证。

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