Combining discrete cosine transform and convolutional neural networks to speed up the Hamiltonian Monte Carlo inversion of pre-stack seismic data     

Mattia Aleardi 《Geophysical Prospecting》2020,68(9):2738-2761

Markov chain Monte Carlo algorithms are commonly employed for accurate uncertainty appraisals in non-linear inverse problems. The downside of these algorithms is the considerable number of samples needed to achieve reliable posterior estimations, especially in high-dimensional model spaces. To overcome this issue, the Hamiltonian Monte Carlo algorithm has recently been introduced to solve geophysical inversions. Different from classical Markov chain Monte Carlo algorithms, this approach exploits the derivative information of the target posterior probability density to guide the sampling of the model space. However, its main downside is the computational cost for the derivative computation (i.e. the computation of the Jacobian matrix around each sampled model). Possible strategies to mitigate this issue are the reduction of the dimensionality of the model space and/or the use of efficient methods to compute the gradient of the target density. Here we focus the attention to the estimation of elastic properties (P-, S-wave velocities and density) from pre-stack data through a non-linear amplitude versus angle inversion in which the Hamiltonian Monte Carlo algorithm is used to sample the posterior probability. To decrease the computational cost of the inversion procedure, we employ the discrete cosine transform to reparametrize the model space, and we train a convolutional neural network to predict the Jacobian matrix around each sampled model. The training data set for the network is also parametrized in the discrete cosine transform space, thus allowing for a reduction of the number of parameters to be optimized during the learning phase. Once trained the network can be used to compute the Jacobian matrix associated with each sampled model in real time. The outcomes of the proposed approach are compared and validated with the predictions of Hamiltonian Monte Carlo inversions in which a quite computationally expensive, but accurate finite-difference scheme is used to compute the Jacobian matrix and with those obtained by replacing the Jacobian with a matrix operator derived from a linear approximation of the Zoeppritz equations. Synthetic and field inversion experiments demonstrate that the proposed approach dramatically reduces the cost of the Hamiltonian Monte Carlo inversion while preserving an accurate and efficient sampling of the posterior probability.  相似文献   

基于EEMD和ARIMA的海温预测模型研究          下载免费PDF全文

张莹  谭艳春  彭发定  廖杏杰  余昱昕 《海洋学研究》2019,37(1):9-14

类型丰富、时空分辨率高的海洋探测数据,为信号分解和机器学习算法的应用提供了可能。本文针对如何建立有效的海温预测模型这一问题,使用高时空分辨率的海表温度(SST)融合产品,引入信号处理领域的集合经验模态分解(EEMD)和机器学习领域的自回归积分滑动平均模型(ARIMA)。首先利用最适于分解自然信号的EEMD方法,将海温数据分解成多个确定频率的序列;再利用ARIMA分别对各个频率的序列进行预测,最后将各个序列的预测结果进行组合。该方法在丰富数据的支撑下,比以往直接使用海温数据所建立的预测模型精度更高,为更好地进行海温预测提供了新方法。  相似文献   

复杂地形景区三维导览图的设计与实现     

吴思锴  李百寿  郭家豪  李雪  张卫平 《北京测绘》2020,(1):38-43

为满足复杂地形景区对三维地图导览的需求,构建更为清晰的三维地图模型,提供良好的三维导览地图设计方案显得尤为重要。为了更好地与卫星影像进行贴合,DEM数据的采样密度要与卫星影像的分辨率一致。本文通过对比当下常用的四种空间插值方法的适用范围与运用特点,设置相关阈值及权重,直观比较了四种插值方法产生的插值结果,选择更适合复杂景区DEM插值的插值方法并对其进行精度提升,以此得到符合精度要求的DEM数据。最后利用相应地区的卫星影像进行地图投影及影像贴图,两种数据结合构建复杂景区的三维地图模型,给游客带来更为精确直观的定位信息和空间要素信息。  相似文献   

基于MATLAB的铁路路基沉降预测优化方法     

刘鹏鹏  李仲勤 《北京测绘》2020,(4):580-583

高速铁路路基的工后沉降严重影响着行车安全。在已有的预测模型中,所采用的初始数据往往不能满足等时间周期采集,而且还会伴随着一系列不可避免的观测误差,模型本身的误差累计,不能进行长期预测。文中利用最小二乘原理对初始值进行拟合改进,采用Lagrange插值方法将非等间隔序列转为等间隔序列,并基于新陈更替GM(1,1)模型利用MATLAB建立沉降预测模型;在此基础上,提出对模型残差进行GM改正以提高模型精度的方法。研究表明,通过对初始值序列改正后的模型具有较好的适应性,优化改进后的模型预测误差小,预测精度优于新陈更替GM(1,1)模型。  相似文献   

黄土高原沟谷地貌发育演化研究进展与展望     

熊礼阳  汤国安 《地球信息科学学报》2020,22(4):816-826

黄土沟谷是黄土地貌中最有活力、最具变化、最富特色的对象单元,黄土高原千沟万壑的地貌形态以及触目惊心的侵蚀状态也让区域内沟谷地貌的形成、发育及演化问题成为研究中焦点及前沿性科学问题。近年来,诸多学者采用地学测年法、特征表达法、监测模拟法力图实现对黄土沟谷发育演化进程中“过去-现代-未来”的科学认知。这些研究在相当程度上丰富了黄土沟谷发育过程的认知。本文梳理了黄土高原沟谷地貌演化相关研究的现状,并从黄土高原地貌演化、黄土沟谷发育、基于DEM的沟谷信息提取与表达等研究进行了系统的回顾、梳理与分析。此外,本文提出“黄土沟道剖面群组”概念与方法,试图从新的视角审视黄土沟谷地貌发育演化过程。沟道剖面在黄土沟谷发育演化进程中传递物质能量和累积地形动力,并通过径流节点的串联实现剖面群的连接与组合,形成独特的剖面“群组”模式;该沟道剖面群组是集黄土沟谷地貌特征与过程于一体的综合信息集成体,其三维空间结构是对黄土沟谷地貌发育演化的高度抽象与映射,并可望进一步丰富黄土高原数字地形分析理论与方法体系,为黄土高原黄土地貌成因机理与空间分异格局带来创新的认识。  相似文献   

基于贝叶斯方法的深层充电效应风险模型评估          下载免费PDF全文

李程  陈东 《地球物理学报》2019,62(6):1991-2000

高能电子穿透航天器并在其内部沉积电荷从而引发深层充电效应,是导致卫星故障的重要因素之一.为了评估深层充电效应诱发卫星异常的风险,本文基于贝叶斯方法,使用一颗地球同步轨道卫星的异常数据和GOES-8卫星的电子通量探测数据,计算了不同能量阈值及累积时间的电子注量、不同卫星配置下模拟仿真的沉积电荷,并分别与卫星异常建立一系列概率风险模型.本文从模型中随机抽样得到模拟异常,并与实测异常构造混淆矩阵以评估模型拟合优度,结果表明1.0MeV电子3日累积注量-卫星异常概率风险模型为该卫星最优模型.本文利用最优模型对该卫星深层充电效应风险进行了计算,在1.0MeV电子3日累积注量达到2.0×10~(10)cm~(-2)·sr~(-1)时,该卫星发生深层充电异常的平均后验概率为27%,且95%最小可信值为22%.根据最优模型,我们对该卫星最可能导致异常的部件的材料和结构等特征做出了推断.  相似文献   

国家安全发展示范城市建设的震灾预防对策研究     

申文庄  贾启超  李峰 《震灾防御技术》2018,13(4):997-1002

我国地震多、强度大、分布广，强地震的现实危害和潜在威胁是我国城市安全发展所面临的重大挑战。国内外城市地震灾害惨痛经验表明，震灾预防能力建设不足的城市往往在强震中毁于一旦。实现我国城市安全可持续发展，必须高度重视和持续推进城市震灾预防能力建设，切实防控和消除地震灾害风险。本文在深入分析城市地震灾害影响因素的基础上，从震灾预防能力建设、城市地震灾害风险防控工作、法规及技术标准和评价体系等方面入手，提出了进一步加强城市震灾预防能力建设的对策建议。  相似文献   

中国西部地区利用烈度数据估计地震动参数的方法   总被引：1，自引：0，他引：1       下载免费PDF全文

陈鲲  俞言祥  高孟潭  亢川川 《地震地质》2014,36(4)

通过最近收集到的中国西部地区的6次地震的地震动参数和烈度数据,建立了该地区适用于贝叶斯方法的各烈度档P(I|GM)的经验分布。利用2011年发生的四川炉霍地震和新疆伽师地震资料验证了依据烈度数据用贝叶斯方法估算峰值加速度的可行性。研究结果还表明,用贝叶斯方法估计的参数精度与选择的先验概率(衰减关系)显著相关。针对这2次地震,用各烈度档地震动参数的均值法、地震动衰减关系法及贝叶斯法3种方法估算的峰值加速度值与峰值加速度观测值之间的均方根比较表明,用贝叶斯方法估算的参数精度优于用另2种方法所获结果。  相似文献   

Anthropogenic land-use signals propagate through stream food webs in a California,USA, watershed     

《Limnologica》2014

Human development of watersheds can change aquatic ecosystems via multiple pathways. For instance, human rural development may add nutrients to ecosystems. We used naturally occurring stable isotopes in stream food webs to investigate how land use affects stream ecosystems across a gradient of land development in the San Lorenzo watershed, California. Road density was used as a proxy for land development. We found that streams in watersheds with higher road densities had elevated concentrations of phosphate and nitrate. Furthermore, algal δ¹⁵N values increased as a function of nitrate concentration, but saturated at approximately 6‰. This saturating pattern was consistent with a two-source mixing model with anthropogenic and watershed sources, fit using Bayesian model fitting. In sites that had >2.6 km roads km⁻², anthropogenic sources of N were estimated to represent >90% of the N pool. This anthropogenic N signal was propagated to stream consumers: rainbow trout (Oncorhynchus mykiss), signal crayfish (Pacifasticus leniusculus), and benthic invertebrate δ¹⁵N were positively correlated with algal δ¹⁵N. Even relatively low density rural human land use may have substantial impacts on nutrient cycling of stream ecosystems.  相似文献   

IntCal13 calibrated ages of the Vedde and Saksunarvatn ashes and the Younger Dryas boundaries from Kråkenes,western Norway          下载免费PDF全文

ØYSTEIN S. LOHNE  JAN MANGERUD  HILARY H. BIRKS 《第四纪科学杂志》2014,29(5):506-507

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