Seismic response analysis of laterally inhomogeneous ground with emphasis on strains

The objective of this paper is to make it clear how strain behaviors are affected by the lateral inhomogeneity of ground based on both theoretical simulation and array observation of earthquake motions. We use a two-dimensional pseudo-spectral method to numerically obtain strain motions as well as acceleration motions. We applied the method to some model grounds, which have typical inhomogeneity in the horizontal direction, to estimate general features of strains and accelerations. In addition, the technique was also applied to a site where subsurface irregularity is typically found and an array observation system of earthquake motions was densely deployed. In the latter application of the method, we placed emphasis on comparisons between the observed and simulated motions.     

Conditional components for simulation of vector random fields

Conditional component random fields (CC) based on Cholesky decomposition of the multivariate spectra are introduced in this study to develop a new method for conditional simulation of vector attributes in environmental and geological phenomena. The CC are independent random fields with covariance models obtained from projections and conditioning in the frequency domain. The approach is to simulate one attribute in the physical space and use the results to estimate the other attributes in the frequency domain. Then, a CC for the next attribute is simulated and projected on the other attributes. In general, any attribute is built as the sum of inverse Fourier transform of the orthogonal projection of previous simulated CC plus a last CC simulated in the physical space. This simulation approach continues in this fashion for several attributes and the order of them may be changed for different realizations. This method allows for data conditioning and simulation. A simplified version for intrinsically correlated random fields allows for an approach that avoids the frequency domain.     

地理标记语言到VML的转换

分析了地理标记语言和矢量标记语言的各自特征，在此基础之上提出了一种从GML格式转换到VML格式的方法，实现了IE中矢量地图的直接显示。最后给出了实例验证。     

中国干旱区土地沙砾化过程的空气流压场分析

在野外调查和资料分析的基础上,应用空气流压场原理,矢量分析法,分析了我国干旱地区不同地貌类型分区的土地沙砾化过程,及其所导致的风蚀,风积地形的分布规律,高山地区,风蚀风积地形从山顶到山木麓呈带状分布,在平坦地区,随气流强弱,扰动,就地就近起沙,形成了低缓沙丘,河湖淤泥平原,土地干裂迭加风力,形成了残丘雅丹地形,在丘陵地区的迎风坡为土地砾化,背风坡为沙化。     

基于机器学习的参考作物蒸散量估算研究

参考作物蒸散量（Reference Evapotranspiration, ET₀）的准确估算对区域水资源管理和分配、流域水量平衡以及气候变化等研究具有重要作用。新疆地处我国西北干旱地区,水资源供需矛盾尖锐,精确估算该地区的ET₀有助于其科学合理地调配水资源,缓解水资源供需压力。FAO推荐的Penman-Monteith法是计算ET₀的标准方法,但该方法需要多项气象因子,而新疆地区气象站点较少且分布不均,精确完备的气象数据在新疆大部分区域难以获取。因此,如何使用有限气象因子获取高精度的ET₀在新疆地区备受关注。本文基于中国气象数据网提供的新疆地区1980—2019年的地面气候资料日值数据集,在日和月尺度下,通过对最高气温T_max、最低气温T_min、平均气温T_avg、风速U₂、相对湿度RH和日照时数n共6项气象因子进行敏感性分析,形成不同的气象因子组合;然后使用SVM、RF、GBDT和ELM 4种机器学习算法,以FAO-56 PM计算值为标准值,对新疆地区的ET₀进行了拟合建模;最后,从拟合精度、稳定性和计算代价3个方面对模型进行评价。研究表明：① 在新疆地区,ET₀对RH、T_max和U₂敏感系数级别为高,平均敏感系数分别为-0.516、0.283和0.266;n为中等,平均敏感系数为0.124;T_min和T_avg为低,平均敏感系数分别为-0.016和-0.003;② 在日尺度,各算法在RH、T_max、U₂和n这4项气象因子为输入时精度较高（RMSE<0.5 mm/day,R²>0.95）,可对ET₀进行精确估算;在月尺度,各算法使用RH、T_max和U₂这3项参数便可对ET₀进行精确估算。SVM和GBDT这2种算法在日尺度和月尺度都有较好的适用性,可在相应尺度下使用较少气象因子替代FAO-56 PM公式对ET₀进行估算。     

基于GANBPSO-SVM的高光谱影像特征选择方法

为了在保持对目标检测和分类分析所需信息的同时,降低高光谱影像的维度,提出了一种混合优化策略的特征选择方法。该方法将遗传算法和二进制粒子群优化算法融合成一种新的混合优化策略（GANBPSO）,自动选择最优波段组合,同时优化分类器支持向量机（RBF-SVM）的参数,以提高分类器的分类性能。为了说明所提出方法的有效性,采用了在高光谱分类中广泛使用的Indian Pines（AVIRIS 92AV3C）数据集进行测试。结果表明所提出方法（GANBPSO-SVM）能够自动选择包含最多信息的特征子集以保证分类精度,而不需要预先设置所需要的特征子集数量,本方法与传统方法相比具有更好的分类效果。     

一种矢量瓦片零水印算法

针对栅格瓦片和矢量地图的零水印算法不能完全应用于矢量瓦片的问题,提出了一种基于色彩特征的SVG矢量瓦片零水印算法:以SVG矢量瓦片的色彩分布概率为重要特征,利用变换和特定的运算将该特征嵌入原始水印图像中形成零水印。由于该算法未对矢量瓦片数据进行任何修改,常见的几何编辑、几何变换、数据压缩、坐标精度约减等不影响水印的提取;因对各色彩特征进行了一定的约简,少量实体的删减也不影响水印的提取。实验结果表明该零水印算法对矢量瓦片生成效率的影响甚少,可以为矢量瓦片版权保护相关研究提供参考。     

Classification and Recognition of Polyhalite in Chuanzhong Based on Support Vector Machine

Polyhalite is mainly solid mineral potassium in Sichuan Basin, The most of polyhalite layer in Sichuan region is impurity, and usually accompanied by layers of gypsum, anhydrite, rock salt, and even deposited in the same layer. Conventional logging interpretation method can only roughly identificate polyhalite layers. Based on the theory of Support Vector Machine and logging interpretation methods,this paper creates prediction model with the input of logging curves, and discriminates the polyhalite reservoirs in the lower-middle Triassic strata. Compared with logging data, the accuracy rate of the discrimination results reaches 90%. According to the prediction model, identification model can be established with the curve features of polyhalite to discriminate pure polyhalite reservoirs, gypsiferous polyhalite reservoirs and polyhalite-gypsum reservoirs, the accuracy rate is 91.78%. The study demonstrates that Support Vector Machine is superior to the method of logging interpretation, and it has broad prospects in potash exploration.     

图像2DRE四叉树—链式码向量的变换算法

本文叙述了图像数据结构的一种变换算法。近年发展起来的四叉树数据结构,是描述图像结构、压缩存储空间等方面的一种好方法;而链式码向量在检测和描述图像区域边界及其形状方面有很多长处。但两种结构各有其缺点,它们互相补充,才能得到较好效果。本文提出并分析了一个从2DRE四叉树得到图像中的区域边界的算法,即2DRE四叉树一链式码向量变换算法(简称Q—V算法)。文中介绍了算法的基础和算法本身,并对其特点和效果进行评价和分析。     

富蕴地震的预报实践与地倾斜异常分析

1987年9月19日富蕴台以北40km处发生了5.8级地震。富蕴台地倾斜于震前一年开始出现中期趋势异常,矢量图形态变化明显偏离正常趋势,异常量级为10~(-6)。其观测资料反映了震前形变前兆异常,从而于6月份提出书面预报意见。文中还对地倾斜的物理机理作了阐述。