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Studies on real-time estimation method of earthquake ground motions under imperfect information

不完善信息下地震地震动实时估计方法研究

基本信息

批准号：
09680448
负责人：
NODA Shigeru
金额：
$ 2.11万
依托单位：
Tottori University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
1997
资助国家：
日本
起止时间：
1997 至 1998
项目状态：
已结题

项目摘要

This study presents a theoretical procedure for efficiently estimating the spatial distribution of earthquake ground motion indices when observed data at some discrete points are available.1. The spatial estimation method of the average of the process over a block whose location and geometry are known was proposed. A theoretical formulation is presented to estimate conditional lognormal stochastic field when observation is made at some discrete points. The optimum estimator and minimized mean-squared estimation error of a block average value are then compared with the results obtained by point kriging when an unknown value at a known location is estimated. Numerical examples were carried out to examine the influence of block size on the optimum estimator and estimated error variance. Except for very small block sizes, the results indicate that the block kriging is critical method.2. The approximate algorithm for stochastic interpolation and extrapolation of conditional non-Gaussian fie … More lds produces a nonlinear unbiased estimator with the characteristic minimum variance of errors. The extended Kalman filtering procedure is then used for solving the conditional estimation problem transformed into the Gaussian stochastic field. A lognormal stochastic field is taken up as an example. The accuracy and efficiency of the proposed method is discussed compared with the theoretical solutions of simple kriging. It is found that the proposed method does not suffer from the difficulties associated with computing the optimum estimator and estimated error variance.3. A theory for evaluating the maximum entropy estimators and their associated entropy indices for conditional non-Gaussian translation stochastic fields was proposed when observation is made at some discrete points. Through analytical development and numerical examples of stochastic fields with the six types of distribution, kriging and maximum entropy techniques for spatial estimation are also compared. It was found that : 1) the maximum entropy estimate and conditional entropy are dependent on the values of observed data ; and 2) the average conditional entropy has an independence on the observations, and is not larger than the average unconditional entropy. Less

本文提出了在有离散点观测资料时有效估计地震地震动指数空间分布的理论方法。提出了一种已知位置和几何形状的块上过程均值的空间估计方法。给出了在一些离散点观测时估计条件对数正态随机场的理论公式。然后将块平均值的最优估计量和最小均方估计误差与点克里格法估计已知位置的未知值的结果进行比较。通过数值算例验证了块大小对最优估计量和估计误差方差的影响。除了非常小的块尺寸外，结果表明块克里格法是关键方法。给出了条件非高斯分布随机插值外推的近似算法，得到了误差方差特征最小的非线性无偏估计量。然后用扩展卡尔曼滤波方法求解转化为高斯随机场的条件估计问题。以对数正态随机场为例。通过与简单克里格理论解的比较，讨论了该方法的精度和效率。结果表明，该方法不存在计算最优估计量和估计误差方差的困难。提出了条件非高斯平移随机场在某些离散点观测时最大熵估计量及其相关熵指标的求值理论。通过对六种分布类型随机场的分析发展和数值算例，比较了克里格和最大熵的空间估计方法。结果表明：1)最大熵估计和条件熵依赖于观测数据的值；2)平均条件熵与观测值无关，且不大于平均无条件熵。少