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针对现有煤与瓦斯突出预测方法存在的不足,考虑检测到的影响煤与瓦斯突出的多种因素数据,建立了煤与瓦斯突出预测的多Agent信息融合模型,实现对煤与瓦斯突出的快速、准确和动态预测。利用基于均值的分批估计融合算法对煤与瓦斯突出指标的多传感器数据进行处理以获取更为准确、可靠的数据以提高预测准确性,应用D-S证据理论解决煤与瓦斯突出预测过程中的不确定性和不精确性问题。通过实例对提出方法进行验证,结果表明所提出的方法预测准确性高,是一种有效的煤与瓦斯突出预测方法。
Aiming at the shortcomings of existing coal and gas outburst forecasting methods and considering the detected data of various factors affecting coal and gas outburst, a multi-agent information fusion model of coal and gas outburst prediction is established to realize the rapid coal and gas outburst prediction , Accurate and dynamic forecasting. Using the mean-based batch estimation fusion algorithm to process the multi-sensor data of coal and gas outburst indicators to obtain more accurate and reliable data to improve the prediction accuracy, DS evidence theory is applied to solve the problem of coal and gas outburst prediction Certainty and inaccuracy issues. An example is given to validate the proposed method. The results show that the proposed method has high prediction accuracy and is an effective prediction method for coal and gas outburst.