基于长短期记忆网络的甘肃舟曲立节北山滑坡变形预测
The Chinese Journal of Geological Hazard and Control(2023)
Abstract
立节镇北山滑坡长期处于蠕动变形状态,已多次发生滑坡、泥石流灾害。监测地表形变,以掌握灾害体地表形变规律,是实现地质灾害预警预报的可靠依据。文章引入一种机器学习模型——长短期记忆网络,通过立节北山监测点位移数据,运用该方法对立节北山滑坡变形进行预测,并且将预测结果与实际数据进行比对和分析。文章预测结果评价指标选用均方根误差、平均绝对误差、决定系数以及可解释方差,其中决定系数和可解释方差均达到0.99,预测值和真实值的拟合均方根误差和平均绝对误差也表现较低,说明长短期记忆网络在立节北山滑坡变形的预测中达到了良好的预测性能。
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Key words
landslide,lstm neural network,predictive analysis,north mountain of lijie,machine learning
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