The mining subsidence prediction with combination of fuzzy inference and neural networks is investigated.
用模糊数学与神经网络结合的方法研究开采沉陷的预测。
The calculation of maximum ground movement and deformation values is an important link in mining induced subsidence prediction.
地表移动与变形极值计算是开采沉陷预计的重要内容。
In China, with coal resource mining in deep-lying being developed, therefore, the main technology problems about prediction and control of surface subsidence are brought out.
随着我国煤炭资源的开采向深部延伸，带来了地表沉陷预测与控制等主要技术难题。
In order to improve the prediction accuracy and visualization for mining-induced subsidence, research was made on the architecture of GIS-based prediction system for mining subsidence.
为了提高开采沉陷预测精度及其可视化程度，对基于G IS的开采沉陷预测系统构架进行了研究。
The tangent of the main influencing Angle is an important parameter for mining subsidence prediction and surface displacement range demarcation.
主要影响角正切是开采沉陷预计的重要参数，对于地表影响范围的确定具有重要的意义。
The tangent of the main influencing Angle is an important parameter for mining subsidence prediction and surface displacement range demarcation.
主要影响角正切是开采沉陷预计的重要参数，对于地表影响范围的确定具有重要的意义。
应用推荐