论文标题
在机器学习方案中使用LiDAR GEODETIC数据进行蠕变或地震之前的土地运动预测的可能性
Possibility of Land Movement Prediction for Creep or before Earthquake Using Lidar Geodetic Data in a Machine Learning Scheme
论文作者
论文摘要
地震预测是地球科学中最受追求的问题之一。为了预测地震及其随后的土地变化而存在不同的地质和地震学方法。但是，在许多情况下，他们的任务失败了。在本文中，我们通过一种新颖的方法解决了公认的地震预测问题。我们使用四维定位时间机器学习计划来估计地震时间及其土地变化。我们介绍了一项针对加利福尼亚州Ridgecrest的研究，2019年地震预测。我们表明，我们方法的准确性约为土地变化的14厘米，地震时间约2天，大约在地震发生前3年以上的数据预测。
Earthquake prediction is one of the most pursued problems in geoscience. Different geological and seismological approaches exist for the prediction of the earthquake and its subsequent land change. However, in many cases, they fail in their mission. In this paper, we address the well-established earthquake prediction problem by a novel approach. We use a four-dimensional location-time machine learning scheme to estimate the time of earthquake and its land change. We present a study for the Ridgecrest, California 2019 earthquake prediction. We show the accuracy of our method is around 14 centimeters for the land change, and around 2 days for the time of the earthquake, predicted from data more than 3 years before the earthquake.
