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21.
为了解隆尧地裂缝目前的发育状况及其对周边地区的影响,采用2019-01~2020-12共31景Sentinel-1影像,基于SBAS-InSAR和Stacking InSAR技术获取隆尧地裂缝及其周边区域的形变时间序列及形变速率分布,进一步采用均质弹性空间模型研究隆尧地裂缝现今滑移状况。结果表明:1)隆尧地裂缝2019~2020年南北两侧的形变速率梯度差达4 cm/a,较2007~2011年5 cm/a的形变速率梯度差有所下降;2)固城店镇、魏家庄镇、官庄镇存在明显的周期性地表形变,但总体趋势仍为沉降;3)建模结果表明,隆尧地裂缝现阶段几乎破裂至地表,滑移速率为27 mm/a,与2007~2011年结果相比深度及滑移速率有所降低,说明现阶段隆尧地裂缝虽仍处于活跃状态,但活跃程度有所减缓。  相似文献   
22.
Microseismic monitoring in the oil and gas industry commonly uses migration‐based methods to locate very weak microseismic events. The objective of this study is to compare the most popular migration‐based methods on a synthetic dataset that simulates a strike‐slip source mechanism event with a low signal‐to‐noise ratio recorded by surface receivers (vertical components). The results show the significance of accounting for the known source mechanism in the event detection and location procedures. For detection and location without such a correction, the ability to detect weak events is reduced. We show both numerically and theoretically that neglecting the source mechanism by using only absolute values of the amplitudes reduces noise suppression during stacking and, consequently, limits the possibility to retrieve weak microseismic events. On the other hand, even a simple correction to the data polarization used with otherwise ineffective methods can significantly improve detections and locations. A simple stacking of the data with a polarization correction provided clear event detection and location, but even better results were obtained for those data combined with methods that are based on semblance and cross‐correlation.  相似文献   
23.
In petroleum exploration and production, it is essential to have good estimations of the uncertainties on the reserves. Uncertainties on the velocity model used during the data processing are of major importance in this estimation. The generation of several velocity fields gives access to a quantified estimation of the uncertainties due to the velocity model inversion. The use of statistical methods helps in generating several important, equiprobable velocity fields, matching all the available velocity information. This paper presents an efficient simulation algorithm to generate instantaneous velocity fields, constrained by the distribution of values measured at the wells, and calibrated by the stacking velocities, taken as root-mean-square velocities. The simulations also match the covariance model given for the instantaneous velocity fields. The method is developed in a simple one-layer case with constant velocity, and then extended to more realistic situations. Finally, a real data application is shown, using data provided by ENI–Agip Division, and the efficiency of the proposed simulation method is discussed.  相似文献   
24.
为了提高机器学习对深基坑地面沉降的预测能力,本文提出了一种基于Stacking集成学习方式的多模型融合的地面沉降预测方法,并以深圳某深基坑为例,采用斯皮尔曼相关性系数对基坑地面沉降的影响因子进行筛选;运用筛选后的8个影响因子建立Stacking深基坑地面沉降预测模型,以验证该方法的适用性。结果表明:Stacking预测模型的平均绝对误差为0.34、平均绝对误差百分比为2.22%,均方根误差为0.13,相较于传统基模型(随机森林、支持向量机和人工神经网络),Stacking预测模型的平均绝对误差、平均绝对误差百分比和均方根误差值皆为最小。  相似文献   
25.
用中国自动站与CMORPH降水产品融合的逐小时降水量网格数据集、全球预报系统(Global Forecasting System, GFS)模式再分析资料,将机器学习特征算法筛选的特征变量作为模型输入数据,运用Catboost模型和以Catboost和随机森林为初级模型、径向基神经网络为次级模型的融合模型预测未来6 h累计降水等级,并应用公平TS评分(Equal Threat Score,ETS)、真实技巧评分(True Skill Statistic,TSS)、混淆矩阵、预报偏差(Bias值)、击中率(Probability of Detection,POD)对预报结果进行检验分析。结果表明:优化变量的输入有利于提高模型的准确率;Catboost模型和融合模型都可以在一定程度上辨别晴雨状况;仅非动力学变量参与的融合模型对雨区预报准确率最高,但容易将暴雨雨区预报得更加广泛。总体而言,融合模型具有更强、更稳定的预报性能,中到暴雨量级预报准确率还待进一步提高。  相似文献   
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