摘要
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。
In view of the problems existing in the prediction methods of coal and gas outburst, a multi-agent information fusion model for quick, dynamic and accurate prediction of coal and gas outburst is given with the measured data relevant to the multiple influencing factors. The data fusion method based on the arithmetic mean and batch estimation is used to filter the collected multi-sensor indicator data to improve the accuracy of prediction. The Dempster-Shafer evidence theory is used to deal with the indefinability and inaccuracy during the prediction of coal and gas outburst. The result shows that the proposed method has high accuracy, which is a practical method to predict coal and gas outburst.
出处
《控制工程》
CSCD
北大核心
2012年第3期431-434,共4页
Control Engineering of China
基金
辽宁省教育厅科学技术研究项目(2008281)
国家自然科学基金项目(50874059)
辽宁工程技术大学青年基金项目(2010073)
关键词
煤与瓦斯突出预测
多AGENT
信息融合
D—S证据理论
prediction of coal and gas outburst
multi-agent
information fusion
Dempster-Shafer evidence theory
