基于GPS和水准数据的微粒群算法联合反演祁连山北缘断裂三维滑动速率

将微粒群算法与位错理论模型相结合，采用中国地壳运动观测网络提供的青藏高原地区2001~2004年GPS测量数据和2000~2006年水准测量数据，通过常规定权和附有相对权比的方法对祁连山北缘断裂的三维滑动速率进行联合反演，并与蚁群算法反演结果进行对比。结果表明，微粒群算法收敛速度快、稳定性高，结合经典位错理论模型，是一种可以有效求解断层三维滑动速率反演问题的优化算法，在大地测量反演领域极具应用潜力。     

米氏凯伦藻细胞表面膜蛋白质组及其对温度变化的响应研究

米氏凯伦藻(Karenia mikimotoi)近年在我国福建、浙江和广东沿海经常形成赤潮,其赤潮不仅影响到海洋生态系统的稳定,也严重威胁到水产养殖以及人类生命健康安全。本论文以米氏凯伦藻为研究对象,建立了米氏凯伦藻细胞表面膜蛋白质荧光标记技术和细胞膜蛋白质提取方法,运用荧光差异凝胶电泳技术(2-DDIGE)对膜蛋白质进行了分析,并研究了米氏凯伦藻的膜蛋白质组及其对环境温度变动的响应。实验共鉴定到44个细胞表面膜蛋白,其中有效注释27个,主要为转运蛋白、HSP70蛋白家族和捕光蛋白等。米氏凯伦藻在20°C条件下的细胞生长和光合作用要明显好于16°C和12°C,但16°C和12°C条件下的差别不大,表明低温限制了米氏凯伦藻的生长。当米氏凯伦藻从12°C快速转移至16°C和20°C时,藻细胞密度和光合作用效率短时间迅速降低,但细胞很快即适应温度变化。细胞膜上的转运蛋白和光合作用蛋白在其适应温度变化中起着重要作用。     

Gully erosion spatial modelling: Role of machine learning algorithms in selection of the best controlling factors and modelling process

This investigation assessed the efficacy of 10 widely used machine learning algorithms (MLA) comprising the least absolute shrinkage and selection operator (LASSO), generalized linear model (GLM), stepwise generalized linear model (SGLM), elastic net (ENET), partial least square (PLS), ridge regression, support vector machine (SVM), classification and regression trees (CART), bagged CART, and random forest (RF) for gully erosion susceptibility mapping (GESM) in Iran. The location of 462 previously existing gully erosion sites were mapped through widespread field investigations, of which 70% (323) and 30% (139) of observations were arbitrarily divided for algorithm calibration and validation. Twelve controlling factors for gully erosion, namely, soil texture, annual mean rainfall, digital elevation model (DEM), drainage density, slope, lithology, topographic wetness index (TWI), distance from rivers, aspect, distance from roads, plan curvature, and profile curvature were ranked in terms of their importance using each MLA. The MLA were compared using a training dataset for gully erosion and statistical measures such as RMSE (root mean square error), MAE (mean absolute error), and R-squared. Based on the comparisons among MLA, the RF algorithm exhibited the minimum RMSE and MAE and the maximum value of R-squared, and was therefore selected as the best model. The variable importance evaluation using the RF model revealed that distance from rivers had the highest significance in influencing the occurrence of gully erosion whereas plan curvature had the least importance. According to the GESM generated using RF, most of the study area is predicted to have a low (53.72%) or moderate (29.65%) susceptibility to gully erosion, whereas only a small area is identified to have a high (12.56%) or very high (4.07%) susceptibility. The outcome generated by RF model is validated using the ROC (Receiver Operating Characteristics) curve approach, which returned an area under the curve (AUC) of 0.985, proving the excellent forecasting ability of the model. The GESM prepared using the RF algorithm can aid decision-makers in targeting remedial actions for minimizing the damage caused by gully erosion.     

基于最大球算法定量表征土体空间孔隙网络

孔隙网络控制着土体渗流、排水固结与基质吸力等重要工程性质。本文介绍了多孔介质孔隙网络最大球建模基本原理与算法。以显微CT扫描振捣干法生成的南京粉砂试样为例,采用最大球算法建立了试样三维重构模型表征单元体(REV)的空间孔隙网络球棍模型,计算得到了样品REV尺度的孔隙网络参数,统计发现,孔隙半径、喉道半径、孔隙配位数、孔隙截面形状因子、喉道截面形状因子与喉道长度等孔隙参数均近似服从正态分布,孔隙体积近似服从衰减型指数分布。孔隙与喉道半径分别分布在100μm与65μm以内,两者数学期望分别为40. 0μm与18. 0μm;配位数分布在25以内,数学期望为5. 1;孔隙与喉道截面形状因子分别分布在0. 01~0. 04与0. 01~0. 05的区间内,两者数学期望分别为0. 019与0. 033;喉道长度分布在100~800μm以内,数学期望为292. 22μm。同时发现,样品中体积小于1. 5×10^7μm^3的小孔隙数量超过90%。本方法可应用于土体细观孔隙结构的定量表征。     

函数模型与随机模型双约束的GPS-InSAR数据融合方法建立三维形变场

针对InSAR技术研究地表三维形变时监测信息不足的问题，以GPS监测信息为先验信息，建立附有随机模型约束的地表三维形变模型。考虑到SAR卫星极轨方式运行导致LOS向观测量对南北向形变不敏感的问题，以GPS南北向形变观测值作为强约束，构建三维形变解算的函数约束条件。模拟数据与西安地区实测数据的计算结果表明，基于随机模型与函数模型共同约束的地表三维形变参数最小二乘解的精度优于仅有函数模型约束或仅有随机模型约束及无任何约束的参数解精度。     

基于CUDA的地震相干体并行算法

相干体技术在地震勘探资料解释方面得到了广泛的应用,由于相干体技术处理的对象是三维地震数据体,所以算法运算时间较长。为了缩短解释周期,本文充分发挥GPU并行计算优势,对C3相干体算法进行并行化分析。从硬盘读取数据到GPU上计算相干值并写入硬盘的整个过程进行分析,剔除了冗余数据的读取,完成了C3相干体算法的并行化设计与实现。最后分别对串行算法与并行算法进行性能测试,结果表明本文设计的并行算法在保证精度的前提下达到了16倍左右的加速比,对加快地震资料解释具有重要意义。     

Determination of Radiogenic 87Sr/86Sr and Stable δ88/86SrSRM987 Isotope Values of Thirteen Mineral,Vegetal and Animal Reference Materials by DS‐TIMS

This work presents new ⁸⁷Sr/⁸⁶Sr and δ^88/86Sr_SRM987 isotopic values of thirteen mineral, vegetal and animal reference materials. Except for UB‐N, all our results are consistent with previously published data. Our results highlight intermediate precisions among the best presently published and a non‐significant systematic shift with the calculated δ^88/86Sr_SRM987 mean values for the three most analysed reference materials in the literature (i.e., IAPSO, BCR‐2 and JCp‐1). By comparison with the literature and between two distinct digestions, a significant bias of δ^88/86Sr_SRM987 values was highlighted for two reference materials (UB‐N and GS‐N). It has also been shown that digestion protocols (nitric and multi‐acid) have a moderate impact on the δ^88/86Sr_SRM987 isotopic values for the Jls‐1 reference materials suggesting that a nitric acid digestion of carbonate can be used without significant bias from partial digestion of non‐carbonate impurities. Different δ^88/86Sr_SRM987 values were measured after two independent Sr/matrix separations, according to the same protocol, for a fat‐rich organic reference material (BCR‐380R) and have been related to a potential post‐digestion heterogeneity. Finally, the δ^88/86Sr_SRM987 value differences measured between animal‐vegetal and between coral‐seawater reference materials agree with the previously published results, highlighting an Sr isotopic fractionation along the trophic chain and during carbonate precipitation.     

基于分区间泛化Kriging近似模型的船舶局部结构形状优化

为提高Kriging近似模型在船舶结构性能多维度响应预测方面的适用性,对常规Kriging近似模型进行分区间泛化改进:一是对设计样本点的各个维度(分量)进行划区,并在每一个分区间内采用最优拉丁超立方(OLhd)取样;二是引入比例系数w1组合高斯与指数型相关函数提高模型对数据的泛化能力,从而在每个划分的区间内建立泛化的Kriging近似模型。通过SCH测试函数,验证了构造的分区间泛化Kriging模型有效性。结合参数化建模和改进Kriging近似模型对某过渡肘板和舱口角隅边界进行形状优化,优化第一阶段由改进的近似模型通过多岛遗传算法得到全局初步的最优解,第二阶段在初步解的基础上缩小优化变量范围,由少量的FEM计算即可在小范围内搜寻到精确的最优设计变量。结果表明:分区间泛化Kriging近似模型在预测多维度响应时较常规Kriging模型预测精度更高;分阶段的形状优化流程在保证极小误差和缩小计算成本的情况下能够得到理想的应力分布和重量优化结果,有助于船舶结构的轻量化研究。     

基于F-范数的不确定性平差模型的解算方法

为提高基于F-范数的不确定性平差模型的解算效率，给出直接迭代算法进行参数估计。该算法无需SVD，解算过程简单且易于编程计算，同时给出迭代不收敛时的SVD-解方程算法。二元线性拟合及沉降观测AR模型的算例结果表明，这2种算法正确可行，与SVD-迭代算法具有等价性。当迭代收敛时，宜使用直接迭代算法，收敛速度更快，解算效率更高；当迭代不收敛时，可釆用SVD-解方程算法。     

改进的最小曲率迭代法在重力剖面数据插值中的应用

基于将约束点也作为待解算结点的思想，对传统最小曲率迭代法进行改进。改进后的方法在待解算结点周围存在约束点时，避免了根据约束点与待解算结点之间的不同关系需要进行分类推导的复杂过程，同时也避免了因使用泰勒展开式进行分解造成的精度损失，提高了解算精度。