Dynamic responses of a sediment-filled valley with a fluid layer subject to incident waves

The diffraction of elastic waves by a sedimentary valley in a homogeneous elastic half-space is studied in this paper. The sediment-filled valley is composed of a fluid layer over a soft soil deposit whose characteristics may be significant and should be carefully considered when designing long span bridges with high piers. The method of analysis adopted in the paper is to decompose the problem into an interior region and an exterior region. In the exterior region, the scattered wave fields are constructed with the linear combinations of two independent sets of Lamb’s singular solutions, i.e., the integralsolutions for two concentrated surface loads in two directions; and their derivatives are used to represent the scattered wave fields. A technique is proposed to calculate the integrals in the wave-number domain based on the method of steepest descent. For the interior region, the wave fields for the fluid layer and soft soil deposit are expressed in terms of wave functions which satisfy the equation of motion. The continuity condition at the interface of the media is satisfied in the least square sense. The effects of geometric topography, soil amplification and fluid layer subject to different types of incident harmonic plane waves are analyzed and discussed..     

Correlation analysis and partial least square modeling to quantify typical minerals with Chang＇E-3 visible and near-infrared imaging spectrometer＇s ground validation data

In 2013, Chang＇E-3 program will develop lunar mineral resources in-situ detection. A Visible and Near-infrared Imaging Spectrometer （VNIS） has been selected as one payload of CE-3 lunar rover to achieve this goal. It is critical and urgent to evaluate VNIS＇ spectrum data quality and validate quantification methods for mineral composition before its launch. Ground validation experiment of VNIS was carried out to complete the two goals, by simulating CE-3 lunar rover＇s detection environment on lunar surface in the laboratory. Based on the hyperspectral reflectance data derived, Correlation Analysis and Partial Least Square （CA-PLS） algorithm is applied to predict abundance of four lunar typical minerals （pyroxene, plagioclase, ilmenite and olivine） in their mixture. We firstly selected a set of VNIS＇ spectral parameters which highly correlated with minerals＇ abundance by correlation analysis （CA）, and then stepwise regression method was used to find out spectral parameters which make the largest contri- butions to the mineral contents. At last, functions were derived to link minerals＇ abundance and spectral parameters by partial least square （PLS） algorithm. Not considering the effect of maturity, agglutinate and Fe~, we found that there are wonderful correlations between these four minerals and VNIS＇ spectral parameters, e.g. the abundance of pyroxene correlates positively with the mixture＇s absorption depth, the value of absorption depth added as the in- creasing of pyroxene＇s abundance. But the abundance of plagioclase correlates negatively with the spectral parame- ters of band ratio, the value of band ratio would decrease when the abundance of plagioclase increased. Similar to plagioclase, the abundance of ilmenite and olivine has a negative correlation with the mixture＇s reflectance data, if the abundance of ilmenite or olivine increase, the reflectance values of the mixture will decrease. Through model validation, better estimates of pyroxene, plagioclase and ilmenite＇s abundances are given. It is concluded that VNIS has the capability to be applied on lunar minerals＇ identification, and CA-PLS algorithm has the potential to be used on lunar surface＇s in-situ detection for minerals＇ abundance prediction.     

地名分词搜索的词典设计与匹配方法研究

阐述了专门用于分词搜索的关键词词典设计,提出了采用逆向最大匹配和权重匹配相结合的方法,实现了更加准确、高效的地名搜索。     

区域似大地水准面确定的最小二乘支持向量机方法

支持向量机(SVM)是近年来发展起来的机器学习的新方法,它较好地解决小样本、非线性、高维数、局部极小点等实际问题.文中研究支持向量机的拓展算法--最小二乘支持向量机(LSSVM),并将其应用于确定大面积复杂似大地水准面.通过工程实例并与神经网络模型和二次曲面多项式拟合模型相比较,验证确定区域似大地水准面的LSSVM方法的有效性.     

基于APSO-SVR-GRU模型的白水河滑坡周期项位移预测

滑坡周期项位移的预测,是研究地质灾害中滑坡变形至关重要的一步。由于单一模型易受偶然因素影响,且无法充分利用有效信息,导致其预测精度不高,适用性不强。基于此,文中提出了一种结合自适应粒子群算法（APSO）、支持向量机回归算法（SVR）、门控神经网络算法(GRU)的组合模型。该模型通过自适应粒子群优化算法对支持向量机回归算法进行参数寻优,确定最优参数组合,然后利用最小二乘法对APSO-SVR模型与GRU模型赋权建立最优权重比组合模型。以三峡白水河滑坡作为研究对象,选取降雨量、库水位及位移量作为周期项位移的影响因子,对模型进行训练验证,结果表明：在白水河滑坡周期项位移预测中,文中所提出的APSO-SVR-GRU组合模型与单一模型相比,具有更高的预测精度和稳定性。     

几何失真对SAR图像匹配的影响及校正方法分析

合成孔径雷达SAR用于图像匹配导航系统,可大大提高导航精度。然而地形起伏和大气干扰等因素使得SAR实时图存在几何失真,降低了匹配性能。通过对SAR实时图几何失真成因分析,提出了一种二维可分离的几何校正方法,并得出方位向几何失真可跟随成像处理预先校正,图像后处理只需校正距离向。利用数字高程模型DEM和正射图模拟得到了3幅具有不同地形特征的SAR实时图,并分别利用3种几何校正方法对其进行统计实验,得到了不同地形SAR实时图几何校正方法选取的准则。     

Using advanced soft computing techniques for regional shoreline geoid model estimation and evaluation

This study aims at evaluating the global geoid model for a regional shoreline fitting using advanced soft computing techniques and global navigation satellite system/leveling measurements. Artificial neural networks, fuzzy logic, and least square support vector machine models are developed and used to fit the global geoid model for the north coastal Egyptian line. In addition, a novel estimation geoid model is designed and evaluated based on the latest global geoid models. The results of the three estimation models show that they can be used to correct the shoreline geoid model, in terms of root mean square error that ranges from 1.7 to 8.5?cm. Moreover, it is found that the least square vector machine model is a competitive approach with certain advantage in solving complex problems represented by missing data.     

改进的单纯形法及其在非线性参数估计中的应用

采用了改进的单纯形法,该算法利用遗传算法的变异操作来增强单纯形法的全局搜索能力,既兼顾了全局收敛性,又具有高效的局部搜索能力。并通过实例验证了该算法的优越性,以及应用于测量上的非线性最小二乘估计的可行性。     

二维视电阻率断面的快速最小二乘反演

快速最小二乘反演是以平滑限定的最小二乘方法为基础,是对二维视电阻率断面进行反演的一种方法。反演过程不需要提供初始模型,在首次迭代时使用一均匀介质地下模型作为初始模型,该模型的视电阻率偏导数值可以用解析法得到。在后面的迭代中,使用了拟牛顿法去修改每一次迭代的偏导数矩阵,避免了偏导数矩阵的直接计算,从而减少了计算时间和存储空间。同时运用牛顿矩阵校正技术解最小二乘方程组也减少了大量的计算时间。总之,该方