A Computational Model for Velocity Separation in Shallow Sea

Based on the hydrodynamical feature and the theoretical velocity profiles of tidal flow and vvind-induced flow in shal-low sea, a computational model is established for the first time, which can separate observed velocity into tidal velocity and wind-induced velocity by use of the least square method. With the model, not only the surface velocities of tidal flow and vvind-induced flow are obtained, but also the bed roughness height is determined and the wind velocity above the wa-ter surface is estimated. For verification of the model, the observed velocity in the Yellow River Estuary and the laborato-ry test is separated, then it is applied to the Yangtze River Estuary. All the results are satisfactory. The research results show that the model is simple in method, feasible in process and reasonable in result. The model is a valid approach to analysis and computation of field dala, and can be applied to separate the observed velocity in shallow sea; at the same time, reasonable boundary conditions of th     

影响b值计算误差的Monte Carlo实验研究

本文假设地震的发生与时间的关系遵循稳态泊松模型,假设地震震级M服从参数为1/β的指数分布,其中β=b/loge,在此基础上生成地震目录.用最小二乘法估算b值,分别从样本数量、震级间隔、震级误差三方面分析b值误差的大小.统计分析结果表明,b值的标准偏差随着样本数量的增多而减小;随着震级间隔的增大而减小;震级误差使b值的标准误差变大.本文可以为利用真实地震目录求b值时选择适当的方法提供参考.     

一种估计观测资料动态误差的方法

给出一种较好的观测资料动态误差估计的方法：单圈改进法，该方法从轨道理论出发，有明确的物理背景，避免了最小二乘拟合阶数和Vondrak平滑法平滑因子不确定性，较为准确地估计了观测资料的动态误差．另外该方法能够反映观测资料的不正常的跳动，对准确地评估观测仪器的性能，进一步改进观测仪器是有益处的．     

回归预测模型的稳健性讨论--以润扬大桥工程为例

经典的LS估计法(least squares estimation,LS estimation)是对每个观测数据都给予相同的权重,由此带来了对于异常值的处理不当,从而影响了回归模型的有效性,本文采用迭代加权最小二乘法来进行稳健估计(RobustEstimation),并基于MATLAB软件结合润扬大桥工程实例说明了此法的有效性。     

参数优化LSSVM的巷道围岩松动圈预测研究

最小二乘支持向量机方法(LSSVM)在处理小样本、高维数、非线性的问题时,具有求解速度快、易于描述非线性关系的优良特性。但是,该方法得到的模型拟合精度和泛化能力依赖于其相关参数,因此,提出基于粒子群优化算法(PSO)的LSSVM参数优选方法。最后,用该模型对巷道围岩松动圈进行了预测研究。结果表明,PSO优化的LSSVM模型具有收敛速度快、计算精度高的特点,说明该模型是合理、有效的。     

Hybrid Estimation of Semivariogram Parameters

Two widely used methods of semivariogram estimation are weighted least squares estimation and maximum likelihood estimation. The former have certain computational advantages, whereas the latter are more statistically efficient. We introduce and study a “hybrid” semivariogram estimation procedure that combines weighted least squares estimation of the range parameter with maximum likelihood estimation of the sill (and nugget) assuming known range, in such a way that the sill-to-range ratio in an exponential semivariogram is estimated consistently under an infill asymptotic regime. We show empirically that such a procedure is nearly as efficient computationally, and more efficient statistically for some parameters, than weighted least squares estimation of all of the semivariogram’s parameters. Furthermore, we demonstrate that standard plug-in (or empirical) spatial predictors and prediction error variances, obtained by replacing the unknown semivariogram parameters with estimates in expressions for the ordinary kriging predictor and kriging variance, respectively, perform better when hybrid estimates are plugged in than when weighted least squares estimates are plugged in. In view of these results and the simplicity of computing the hybrid estimates from weighted least squares estimates, we suggest that software that currently estimates the semivariogram by weighted least squares methods be amended to include hybrid estimation as an option.     

High-precision geoid determination in small areas: A case study in Doñana National Park (Spain)

Doñana National Park is an area of approximately 500 km² located on the SW coast of Spain that shows one of the greatest geoid gradients on the entire Iberian Peninsula, due to its peculiar tectonic characteristics. So, it is necessary to elaborate an accurate geoid model that can be used with GPS for precise surveying, since the existing ones are insufficient, due to their poor resolution and their limited adaptation to a small area with such a strong gradient. The least squares prediction method was tested in order to obtain the undulation from GPS/orthometric points. The results obtained were unsatisfactory because of the strong geoid gradient. In order to improve accuracy the remove-restore technique was used. Global geopotential model EIGEN-CG01C and a Digital Elevation Model (DEM) with a 25 × 25 m resolution and an accuracy better than 3 m were used. Thus, the final geometrical geoid obtained reaches the precision required by other disciplines (3 cm in any point within the Park). Particularly, the geoid model has allowed for the acquisition of a precision DEM that is essential to formulate a hydrodynamic model for the Doñana marsh functions.     

元素测井产额计算及影响因素分析

元素测井是非常规储层测井评价的主要测井方法之一.元素测井是以元素测量为基础,从矿物成分的角度提供地层信息,有效地将测井资料与地质信息结合起来.元素产额获取会受地层矿物和井眼环境的影响.为了提高元素产额计算的准确性,有必要对影响元素产额计算的因素进行分析.本文利用蒙特卡罗方法分析加权最小二乘逆矩阵法在地层矿物相对复杂的情况下求取元素产额时,地层减速作用、地层俘获作用、地层密度与井眼尺寸对元素产额计算精度的影响.研究结果表明,地层密度对元素产额计算的精度影响较大,地层密度越低,地层元素之间的相互影响越大,使得元素产额计算的误差变大,而元素产额计算受地层减速作用与地层俘获作用的影响较小,仅在地层减速能力较弱或地层俘获作用较强时对元素产额计算有一定影响,井眼尺寸对元素产额计算的精度影响取决于井内介质.     

地震序列较强余震灰色及最小二乘拟合预测方法的应用研究

在收集、整理1966年～2002年8月我国(主要为大陆地区)183个5级以上地震序列资料的基础上，应用灰色预测和最小二乘拟合预测方法，对每一地震序列较强(显著)余震发震时间进行“硬性”检验预测。结果表明，2种预测方法对7级以上地震序列和6级地震序列的较强(显著)余震具有较好的预测效能，预测效能分别为76．2％和64．7％；而对5级地震序列预测效果则不甚明显。因此，灰色预测和最小二乘拟合预测方法主要着眼于对大(强)地震的较强(显著)余震预测，可望在地震现场大(强)震应急工作中发挥积极作用。     

地震序列较强余震最小二乘拟合预测的方法研究

本研究给出了针对地震序列较强余震发生时间进行快速预测的一种方法,即最小二乘拟合预测方法.该方法包括:最小二乘拟合预测模型的建立、预测模型的各种可信性检验及模型预测等内容.震例研究表明,该方法在大(强)地震现场震情分析中可望发挥积极作用.