动态最小二乘支持向量机学习算法     

邓兴升  花向红 《武汉大学学报(信息科学版)》2008,33(11):1122-1125

针对大样本集的训练问题和动态训练样本的模型更新问题,提出了动态最小二乘支持向量机学习算法.该算法充分利用已建好的模型,逐渐加入新样本,并可删除位于任何位置的非支持向量,避免了矩阵求逆运算,保证了算法的高效率.大坝变形及电离层延迟两个时间序列的预报实例表明,该算法具有计算时间短、预报精度高的特点.  相似文献   

基于改进PSO-SVM的噪声稳健建筑物变形监测方法     

张建奇 《北京测绘》2021,35(2):166-171

对高层、超高层建筑物进行实时,高精度的变形监测对提前预防安全隐患,保证人民生命财产安全具有重要意义。建筑物变形作为一种典型的随机性和微弱性过程,噪声等误差的存在会影响从中提取有用的变形信息。针对该问题,提出一种改进粒子群(Particle Swarm Optimization,PSO)算法优化支持向量机(Support Vector Machine,SVM)的噪声稳健建筑物变形监测方法,利用改进PSO算法的全局搜索能力对SVM的核参数进行优化,提升预测精度的同时增强算法的噪声稳健性。基于实测数据的试验结果表明,相对于传统交叉验证SVM和小波方法,所提方法可以获得更高的变形预测精度,并且在低信噪比条件下优势更加明显。  相似文献   

VML在WebGIS图形显示中的应用研究   总被引：3，自引：0，他引：3  

周泽兵 《测绘信息与工程》2005,30(3):12-13

针对目前被动式WebGIS地图显示的局限,提出了引入VML的解决办法,使客户端容易实现矢量地图显示、地物动态变化显示、专题制图显示等,丰富了WebGIS的地图表现方式。  相似文献   

一种基于核学习的储集层渗透率预测新方法   总被引：2，自引：1，他引：2  

杨斌  匡立春  施泽进  孙中春 《物探化探计算技术》2005,27(2):119-123

基于核学习的支持向量机,是一种采用结构风险最小化原则代替传统经验风险最小化原则的新型统计学习方法,具有完备的理论基础。这里提出了核学习技术在储集层非均质特性描述中渗透率参数预测的新用途。在复杂地层中,基于支持向量机的智能和自适应模式识别能力而建立了常规测井多参数信息输入的渗透率预测模型,然后对实际油田储集层渗透率进行了预测。与常规线性回归模型预测结果相对比,所提出的方法更易于使用,很少受不确定因素的影响,并具有较强的信息整合能力以及更高的预测准确性和可信度。  相似文献   

航空影像分割的最小二乘支持向量机方法   总被引：5，自引：0，他引：5  

徐芳  梅文胜  张志华 《武汉大学学报(信息科学版)》2005,30(8):694-698

将最小支持向量机LS-SVM用于航空影像的分割,讨论了不同核函数对分割结果的影响和稀疏化处理对决策函数的影响。试验表明了LS-SVM方法用于航空影像分割的可行性。  相似文献   

Combination of Dependent Realizations Within the Gradual Deformation Method     

Lin Y. Hu 《Mathematical Geology》2002,34(8):953-963

Gradual deformation is a parameterization method that reduces considerably the unknown parameter space of stochastic models. This method can be used in an iterative optimization procedure for constraining stochastic simulations to data that are complex, nonanalytical functions of the simulated variables. This method is based on the fact that linear combinations of multi-Gaussian random functions remain multi-Gaussian random functions. During the past few years, we developed the gradual deformation method by combining independent realizations. This paper investigates another alternative: the combination of dependent realizations. One of our motivations for combining dependent realizations was to improve the numerical stability of the gradual deformation method. Because of limitations both in the size of simulation grids and in the precision of simulation algorithms, numerical realizations of a stochastic model are never perfectly independent. It was shown that the accumulation of very small dependence between realizations might result in significant structural drift from the initial stochastic model. From the combination of random functions whose covariance and cross-covariance are proportional to each other, we derived a new formulation of the gradual deformation method that can explicitly take into account the numerical dependence between realizations. This new formulation allows us to reduce the structural deterioration during the iterative optimization. The problem of combining dependent realizations also arises when deforming conditional realizations of a stochastic model. As opposed to the combination of independent realizations, combining conditional realizations avoids the additional conditioning step during the optimization process. However, this procedure is limited to global deformations with fixed structural parameters.  相似文献   

A Bayes filter in Friedland form for INS/GPS vector gravimetry     

B. Schaffrin  J. H. Kwon 《Geophysical Journal International》2002,149(1):64-75

  相似文献   

Sensitivity Analysis of a Feedforward Neural Network for Considering Genetic Mechanisms of Kuroko Deposits     

Matsuda  Setsuro  Koike  Katsuaki 《Natural Resources Research》2003,12(4):291-301

Exploration for volcanogenic massive sulfide deposits of the kuroko-type is underway in many places. Clarifying the spatial patterns of the metals in kuroko deposits will be useful for understanding their genetic mechanisms and for future exploration of such types of deposits. This study represents a spatial distribution analysis on the contents of principal metals of kuroko deposits: Cu, Pb, and Zn, in the Hokuroku district, northern Japan, by a feedforward neural network and 1917 sample data at 143 drillhole sites. The network, which consists of three layers, was trained by the principle of SLANS in which the numbers of neurons in the middle layer and training data are changed to improve estimation accuracy. Using the weight coefficients connecting adjacent neurons, sensitivity analysis of the neural network was carried out to identify factors influencing spatial distributions of the three metals. The coordinates depth (z) direction, Bouguer gravity, and specific lithology such as dacite were determined to be influencing factors. The high frequency of the z coordinate signifies that the metal contents differ to a large extent by depth. The sensitivity vector was defined using sensitivity coefficients for x, y, and z coordinates of an estimation point. We determined that the directions of large vectors were different inside and outside of the Hanawa-Ohdate area. This characteristic is considered to originate from the differences in the permeability of fractures that became the paths for rising ore solutions, and the depths that the solutions mixed with sea water.  相似文献   

基于信息块法的矢量符号库的建立和符号化实现   总被引：3，自引：1，他引：3  

吴丽春  胡鹏 《武汉大学学报(信息科学版)》2003,28(5):600-603

基于试验成果，详细介绍了基于信息块法的矢量地图符号库的建立和空间信息的符号化。  相似文献   

无拓扑矢量数据快速压缩算法的研究与实现   总被引：17，自引：0，他引：17  

王净  江刚武 《测绘学报》2003,32(2):173-177

首先论述传统矢量数据压缩算法：道格拉斯—普克法，分析将其应用于多边形边界数据压缩所造成的图形失真现象，在此基础上提出一种针对无拓扑矢量数据的快速压缩算法，并在MapInfo环境中实现该算法。  相似文献