共查询到19条相似文献，搜索用时 156 毫秒
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建立回归模型常采用最小二乘方法并忽略自变量观测误差。尽管同时顾及自变量和因变量观测误差的总体最小二乘方法近年来得到了广泛研究,但在模型预测时,依然忽略了待预测自变量的观测误差。对此,本文提出了一种严格考虑所有变量观测误差的无缝线性回归和预测模型,该模型将回归模型的建立和因变量预测联合处理,在建立回归模型过程中对待预测自变量的观测误差进行估计并修正,从而提高了模型预测效果。理论证明,现有的几种线性回归模型都是无缝线性回归和预测模型的特例。试验结果表明,无缝线性回归和预测模型的预测效果优于现有的几种模型,尤其在变量观测误差相关性较大时,无缝模型对预测效果的改善更为显著。 相似文献
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支持向量回归辅助的GPS/INS组合导航抗差自适应算法 总被引：1，自引：0，他引：1
卡尔曼滤波残差分量受到观测信息误差和动力学模型误差的双重影响,由于GPS/INS松耦合导航系统中观测值个数少于状态参数个数,导致异常检测时难以正确区分误差来源,提出一种支持向量回归辅助的组合导航抗差自适应算法。该算法克服了组合系统观测信息无冗余情况下异常检测的局限性,基于遗传算法参数寻优构建回归模型,预测次优观测值,结合整体异常检验法自主选择抗差或自适应滤波,进而调整观测值或动力学模型对导航解的贡献,进行导航预报。最后利用车载实测数据进行验证,结果表明：该算法能够对存在的异常故障智能判定,减弱观测值异常和动力学模型误差影响,保证组合导航精度,提高导航解可靠性。 相似文献
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《武汉大学学报(信息科学版)》2010,(8)
基于预测残差分析和滤波误差估计,提出了一种新的Kalman滤波模型误差的修正方法。该方法在预测残差分析的基础上,利用观测模型误差和动力学模型误差的相互影响,基于滤波误差估计,从修正观测模型入手,有效地消除了以往历元所有观测模型误差和动力学模型误差对当前历元滤波值的影响。GPS动态导航模拟实验表明,该方法不仅有效地消除了整个Kalman滤波模型误差的影响,而且结果比较理想。 相似文献
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针对时间序列自回归(AR)模型在高层建筑物沉降预测中出现的对于历史资料分析和利用不充分的情况,提出了一种基于傅里叶时频分析的沉降预测模型。以桂林市某在建的高层建筑物的沉降变形为例,在分别从时域和频域两个方面充分分析资料的基础上,对建筑物的沉降观测数据进行建模分析,得到了均方误差为0.107 9 mm的预测精度,很好地克服了AR模型在应用中存在的问题,提高了预测精度。 相似文献
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基于误差平方和最小准则构建回归分析模型和时间序列模型的组合模型,采用BP(black propagation)神经网络优化其组合模型的预测结果,最终获得信息最大化的预测结果.将此方法应用于南京地铁某号线自动化监测,结果显示其预测精度高于任何单一模型,预测精度得到有效提升. 相似文献
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顾及框架点坐标误差的三维基准转换严密模型 总被引：1，自引：1，他引：0
框架点坐标是由观测数据通过平差得到的,不可避免地受到观测误差的影响。针对原框架和目标框架坐标均存在误差、非公共点与公共点间存在相关性,以及转换系数矩阵中仅部分元素存在误差的实际情况,提出了同时考虑框架内误差以及转换点间相关性的基准转换严密模型,该模型将公共点和非公共点联合处理,同时计算坐标转换参数和所有点的坐标转换值,推导出了新的严格坐标转换公式,该公式为传统坐标转换公式基础上增加一改正量的形式;进一步,推导了原框架和目标框架坐标的方差不一致情况下的坐标转换模型的自适应解法;最后,利用"陆态网络工程"2000个区域站的实测坐标进行坐标转换验证,结果表明,这种严密模型较传统坐标转换模型具有更高的坐标转换精度。 相似文献
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TAO Benzao ZHANG Chaoyu 《地球空间信息科学学报》2005,8(3):189-192
IntroductionAdjust ment process deals with the problemsfor esti mating parameters and assessing precisionbased on observations with errors . The researchon adjust ment system involves building mathmodel , determining the opti mization rule andstudying adjust ment arithmetic . Math model ofadjust ment system(also called adjust ment mod-el)is composed of functional and stochastic mod-els . The former describes the relationship be-tween observations and the expectation of pa-rameters . The latte… 相似文献
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Some theory problems affecting parameter estimation are discussed in this paper. Influence and transformation between errors of stochastic and functional models is pointed out as well. For choosing the best adjustment model, a formula, which is different from the literatures existing methods, for estimating and identifying the model error, is proposed. On the basis of the proposed formula, an effective approach of selecting the best model of adjustment system is given. 相似文献
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A new method through Gauss–Helmert model of adjustment is presented for the solution of the similarity transformations, either 3D or 2D, in the frame of errors-in-variables (EIV) model. EIV model assumes that all the variables in the mathematical model are contaminated by random errors. Total least squares estimation technique may be used to solve the EIV model. Accounting for the heteroscedastic uncertainty both in the target and the source coordinates, that is the more common and general case in practice, leads to a more realistic estimation of the transformation parameters. The presented algorithm can handle the heteroscedastic transformation problems, i.e., positions of the both target and the source points may have full covariance matrices. Therefore, there is no limitation such as the isotropic or the homogenous accuracy for the reference point coordinates. The developed algorithm takes the advantage of the quaternion definition which uniquely represents a 3D rotation matrix. The transformation parameters: scale, translations, and the quaternion (so that the rotation matrix) along with their covariances, are iteratively estimated with rapid convergence. Moreover, prior least squares (LS) estimation of the unknown transformation parameters is not required to start the iterations. We also show that the developed method can also be used to estimate the 2D similarity transformation parameters by simply treating the problem as a 3D transformation problem with zero (0) values assigned for the z-components of both target and source points. The efficiency of the new algorithm is presented with the numerical examples and comparisons with the results of the previous studies which use the same data set. Simulation experiments for the evaluation and comparison of the proposed and the conventional weighted LS (WLS) method is also presented. 相似文献
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Some theory problems affecting parameter estimation are discussed in this paper. Influence and transformation between errors
of stochastic and functional models is pointed out as well. For choosing the best adjustment model, a formula, which is different
from the literatures existing methods, for estimating and identifying the model error, is proposed. On the basis of the proposed
formula, an effective approach of selecting the best model of adjustment system is given.
Project supported by the Open Research Fund Program of the Key Laboratory of Geospace Environment and Geodesy, Ministry of
Education, Wuhan University (No. 905276031-04-10). 相似文献
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Rolf König 《Journal of Geodesy》1990,64(2):111-125
In the adjustment of inertial position surveys the additional parameters describing the systematic errors of individual traverses
can be considered as deterministic or stochastic. The paper deals with various aspects of the deterministic or stochastic
approach by way of a standard functional model. If purely deterministic parameters are set up, the solvability of the least
squares problem depends on redundant observations like coordinate discrepancies of forward and backward runs or coordinate
differences at cross-over points of traverse networks. Inequalities are presented to handle the configuration problem for
any net and for several ways of introducing parameter sets. Also condition equations being geometrically explainable are developed
solving the datum problem in free adjustment applications.
Based on the Ebersberger Forst campaigns with a large amount of Ferranti, Honeywell and Litton data, numerical investigations
into the stochastic properties of the additional parameters and the observations follow. It turns out that additional parameters
for Honeywell and Litton data can be considered as stochastic parameters while for Ferranti data significant azimuth and time
dependent effects can be found. The investigations of true errors show that in case of the deterministic adjustment approach
a diagonal covariance matrix can be introduced and in case of stochastic additional parameters a first order Gauss-Markov
process serves as a good approximation for the stochastic behaviour of the observations. 相似文献
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On symmetrical three-dimensional datum conversion 总被引：2，自引：0，他引：2
A 3-D similarity transformation is frequently used to convert GPS-WGS84-based coordinates to those in a local datum using
a set of control points with coordinate values in both systems. In this application, the Gauss-Markov (GM) model is often
employed to represent the problem, and a least-squares approach is used to compute the parameters within the mathematical
model. However, the Gauss–Markov model considers the source coordinates in the data matrix (A) as fixed or error-free; this is an imprecise assumption since these coordinates are also measured quantities and include
random errors. The errors-in-variables (EIV) model assumes that all the variables in the mathematical model are contaminated
by random errors. This model may be solved using the relatively new total least-squares (TLS) estimation technique, introduced
in 1980 by Golub and Van Loan. In this paper, the similarity transformation problem is analyzed with respect to the EIV model,
and a novel algorithm is described to obtain the transformation parameters. It is proved that even with the EIV model, a closed
form Procrustes approach can be employed to obtain the rotation matrix and translation parameters. The transformation scale
may be calculated by solving the proper quadratic equation. A numerical example and a practical case study are presented to
test this new algorithm and compare the EIV and the GM models. 相似文献
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加权整体最小二乘方法是一种能同时顾及EIV（errors-in-variables）模型中系数矩阵和观测向量误差的参数估计方法。根据不同的应用场景,EIV模型则表现出不同的结构特征。"加权整体最小二乘EIO模型与算法"一文采用EIO模型处理EIV模型中的结构化问题*。为了将其与现有方法进行对比,本文罗列出4种处理EIV模型结构特征的方法,并归纳了8种参数估计公式。同时从精度评定的角度讨论了整体最小二乘解的一阶及更高阶精度近似评定方法。需要强调的是,针对EIV模型及其参数估计理论可以从函数模型、随机模型和参数估计方法3个方面展开研究,但各方法殊途同归。 相似文献