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作 者:牟全斌[1]
机构地区:[1]煤炭科学研究总院西安研究院,陕西西安710054
出 处:《煤炭科学技术》2009年第9期44-47,共4页Coal Science and Technology
摘 要:针对传统数学模型在处理煤与瓦斯突出问题上存在的弊端,通过对工作面进行网格划分,并借助人工神经网络建立工作面突出区域预测的非线性模型,减少人为因素的干扰,实现多指标定量预测,大幅提高了预测精度和准确度,为工作面防突措施的制订和执行提供科学依据。According to the disadvantages existed in the coal and gas outburst control with the conventional mathematical model, and through the mesh generation of the coal mining face, the artificial neural networks was applied to establish a nonlinear model to predict outburst area of the coal mining face. The interferences of the human factors was reduced. The quantitative prediction of the multi index could be conducted and the prediction accuracy and correction were highly improved. All those could provide the scientific basis for out- burst control measures made and implemented for the coal mining face.
关 键 词:工作面 突出区域预测 网格划分 人工神经网络 预测模型
分 类 号:TD713.2[矿业工程—矿井通风与安全]
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