CAJ | 학술논문

随着全球经济的发展,天然资源受到了过度的开采,使得地质灾害日益严重。而地面变形塌陷灾害是一种很重要的地质灾害。为了减少矿区周围危害的发生,本论文利用GPS对矿山地表岩移观测得到的数据,采用MATLAB神经网络方法建立GPS数据时间序列预测模型,并且成功的预测出了未来一期的地表移动变化。应用结果表明,神经网络是很好的处理非线性动态数据,能够反映出要素之间的非线性关系,计算精度高,预测准确度高,具有较强的实用性。
수착전구경제적발전,천연자원수도료과도적개채,사득지질재해일익엄중。이지면변형탑함재해시일충흔중요적지질재해。위료감소광구주위위해적발생,본논문이용GPS대광산지표암이관측득도적수거,채용MATLAB신경망락방법건립GPS수거시간서렬예측모형,병차성공적예측출료미래일기적지표이동변화。응용결과표명,신경망락시흔호적처리비선성동태수거,능구반영출요소지간적비선성관계,계산정도고,예측준학도고,구유교강적실용성。
With the global economic development, natural resources have been over--exploitation, the increasingly serious geological disasters. In order to reduce the occurrence of hazards around the mines, we use the date of GPS observation on the mine surface moving and use the forecasting model of MATLAB neural network to establish the GPS data time series and success predict a change of future in ground movement. The application results is show that the neural network is a good way to deal with the nonlinear dynamic data, it can reflect the nonlinear relationship between the elements with high precision, forecast accuracy and has strong practicability.