四柏树水源地三维水文地质数值模拟中的参数最优估计

水文地质数值模拟中参数估计的方法较多,但大多对非线性问题的适应性较差。在陕西省靖边县四柏树水源地三维水文地质数值建模中,选用独立于模型本身的非线性系统加权最小二乘方法,对模型中的水文地质参数(K,μ,Ss)进行最优化估计,取得了较好的效果。     

非参数回归法在孔隙度参数预测中的应用

目前有很多利用地震属性进行储层参数预测的方法,多数方法都是针对一种特定的参数模型而制定的统计方法,即只有在一定的参数模型中才能使用的统计方法.实际应用中,由于地震属性与储层参数之间的关系十分复杂,事先无法给出合适的、具体的参数模型,使用参数模型就有可能产生较大误差.本文简要介绍了非参数回归预测方法的基本原理和方法特点,对如何分析和选取具有明确物理意义的、反映储层参数横向变化较为敏感的、与储层参数关系较为密切的地震属性进行了讨论.用非参数回归法对大港唐家河工区进行了孔隙度参数的平面分布预测,表明该方法在储层参数预测技术以及油藏描述中将会有广阔的应用前景.     

多支护结构在深圳珠江广场深基坑工程中的应用

通过深圳珠江广场深基坑工程实例,介绍了根据场地周边不同条件分别采用不同支护方案的设计思路。在该工程中，多支护结构的综合利用成功地在复杂的施工环境下保证了基坑和周围建筑群及地下管线的安全，而且降低了成本，缩短了工期。     

适用于袖珍计算机频率测深数字滤波方法

详细推导了电偶源频率测深单分量电场定义的视电阻率数字滤波计算公式,并且应用最小二乘法设计了只有30个系数的滤波器,编制出适用于袖珍计算机的视电阻率计算程序,使计算速度大为提高.与用均匀半空间的精确公式计算的视电阻率对比,最大相对误差<2%.     

地形描绘方法在黄土丘陵沟壑地区的应用

本文探讨了地形描绘方法在地学中的应用效果。通过在山西黄土丘陵沟壑地区描绘河流沟网分布的多种比较计算可知,利用数字高程模型,用离散余弦变换进行小分面拟合以及导数分析,并注意选择适当小的拟合分面和在可能条件下提高信息源的分辨率,就可以得到较好的结果。这项工作对于产生地理信息系统数字地形模型的派生数据源是有意义的。     

The Use of Second-generation Wavelets to Combine a Gravimetric Quasigeoid Model with GPS-levelling Data

The merging of a gravimetric quasigeoid model with GPS-levelling data using second-generation wavelets is considered so as to provide better transformation of GPS ellipsoidal heights to normal heights. Since GPS-levelling data are irregular in the space domain and the classical wavelet transform relies on Fourier theory, which is unable to deal with irregular data sets without prior gridding, the classical wavelet transform is not directly applicable to this problem. Instead, second-generation wavelets and their associated lifting scheme, which do not require regularly spaced data, are used to combine gravimetric quasigeoid models and GPS-levelling data over Norway and Australia, and the results are cross-validated. Cross-validation means that GPS-levelling points not used in the merging are used to assess the results, where one point is omitted from the merging and used to test the merged surface, which is repeated for all points in the dataset. The wavelet-based results are also compared to those from least squares collocation (LSC) merging. This comparison shows that the second-generation wavelet method can be used instead of LSC with similar results, but the assumption of stationarity for LSC is not required in the wavelet method. Specifically, it is not necessary to (somewhat arbitrarily) remove trends from the data before applying the wavelet method, as is the case for LSC. It is also shown that the wavelet method is better at decreasing the maximum and minimum differences between the merged geoid and the cross-validating GPS-levelling data.     

Application of Wavelet Decomposition to Removing Barometric and Borehole Water Tidal Response in Level

Wavelet decomposition is used to analyze barometric fluctuation and earth tidal response in borehole water level changes. We apply wavelet analysis method to the decomposition of barometric fluctuation and earth tidal response into several temporal series in different frequency ranges. Barometric and tidal coefficients in different frequency ranges are computed with least squares method to remove barometric and tidal response. Comparing this method with general linear regression analysis method, we find wavelet analysis method can efficiently remove barometric and earth tidal response in borehole water level. Wavelet analysis method is based on wave theory and vibration theories. It not only considers the frequency characteristic of the observed data but also the temporal characteristic, and it can get barometric and tidal coefficients in different frequency ranges. This method has definite physical meaning.     

一种多圆目标的联合检测方法

本文针对现有的几种用于圆检测的方法在检测多个圆时效果不理想,提出了一种运用Hough变换和最小二乘拟合联合检测的新的圆检测方法,它是首先用改进的Hough变换进行粗检测,再用最小二乘拟合进行精确检测,既利用了Hough变换检测多个圆的优势,又利用了最小二乘拟合不能检测多个圆但检测精度高的特点,所以该方法对于多个圆的检测,具有较强的适应能力。     

基于灰色系统与线性回归方法的水质预测

以北京市石景山区某地地下水监测点多年监测数据为例,进行适宜性预测方法的验证。其中,总硬度灰色预测值的平均相对误差为2.62%比线性预测低5.65个百分点;溶解性总固体线性预测值的平均相对误差为2.33%比灰色预测低0.61个百分点,与通过拟合度R~2值大小选取的最优预测方法一致,表明通过拟合度R~2值大小来选取合理的预测方法是一种便捷、合理的技术手段。     

Prediction of the presence of topsoil nitrogen from spaceborne hyperspectral data

Conventional methods of soil nitrogen extraction are time consuming, expensive and tedious. Remote sensing and Geographical Information System technologies can be used for the rapid and efficient prediction of the presence of soil nitrogen. However, studies are limited by and large to fields of larger and homogeneous units. This research concentrates on the prediction of topsoil nitrogen from harvested, scattered and small-sized agricultural fields of India using hyperspectral data. Spaceborne hyperspectral Hyperion data are used for the prediction of the presence of nitrogen. Multivariate partial least square regression method was used to predict the presence of nitrogen from reflectance. Reflectance data were pretreated using moving average and Savitzky–Golay filters which resulted in moderate prediction of R² 0.65 and 0.63 for calibration and validation, respectively. It can be inferred that Hyperion data can be effectively used for the prediction of the presence of soil nitrogen with a moderate level of accuracy even in case of scattered fields and fields of sizes approximately equal to the spatial resolution of the satellite.