利用GOCE卫星轨道数据恢复地球重力场模型方法的分析

欧空局早期公布的时域法和空域法解算的GOCE模型均采用能量守恒法处理轨道数据, 但恢复的长波重力场信号精度较低, 而且GOCE卫星在两极存在数据空白, 利用其观测数据恢复重力场模型是一个不适定问题, 导致解算的模型带谐项精度较低, 需进行正则化处理。本文分析了基于轨道数据恢复重力场模型的方法用于处理GOCE数据的精度, 对最优正则化方法和参数的选择进行研究。利用GOCE卫星2009-11-01—2010-01-31共92 d的精密轨道数据, 采用不依赖先验信息的能量守恒法、短弧积分法和平均加速度法恢复GOCE重力场模型, 利用Tikhonov正则化技术处理病态问题。结果表明, 平均加速度法恢复模型的精度最高, 能量守恒法的精度最低, 短弧积分法的精度稍差于平均加速度法。未来联合处理轨道和梯度数据时, 建议采用平均加速度法或短弧积分法处理轨道数据, 并且轨道数据可有效恢复120阶次左右的模型。Kaula正则化和SOT处理GOCE病态问题的效果最好, 并且两者对应的最优正则化参数基本一致, 但利用正则化技术不能完全抑制极空白问题的影响, 需要联合GRACE等其他数据才能获得理想的结果。     

泥质砂岩激发极化弛豫时间谱的正则化反演

激发极化衰减谱是一系列单指数衰减的线性叠加,因此可以对衰减谱进行多指数反演,得到的弛豫时间谱可用于储层孔隙结构和渗透性评价,是一种非常有前途的技术。由于实际测井的信噪比相对较低,常规的奇异值分解方法难以获得合理的弛豫时间谱,为此,采用正则化约束,结合奇异值分解,对合成数据和实际测量的衰减谱进行反演,得到连续的弛豫时间谱;同时,讨论了弛豫时间谱的时间常数分布、正则化因子以及信噪比对反演结果的影响。研究结果表明:该方法适用于信噪比较低的实际测量结果的反演,弛豫时间常数的分布点数为32~64较为合适;随着正则化因子的增加,反演结果逐渐变得平滑,存在一个最优的正则化因子,用于获得最为合理的弛豫时间谱;在双对数图中,最优正则化因子随着信噪比的增加而线性降低,因此通过测量结果的信噪比,可以求取最优正则化因子,进而将该技术应用于实际。     

基于分形先验信息的非线性反演

基于分形先验信息的非线性反演方法能综合利用测井数据和地震信息,在贝叶斯框架下,通过分形高斯噪音算法得到基于分形理论的先验信息,然后根据地震资料构建似然函数,最终利用基于快速模拟退火算法(Very Fast Simulated Annealing,VFSA)改进的粒子群优化(Particle Swarm Optimization,PSO)算法(VFSA-PSO)实现后验概率密度的抽样。与确定性反演结果相比,该方法能够有效地融合测井资料中的高频信息,提高反演结果的分辨率,并且目标函数的建立融合了确定性反演中的低频约束,从而得到宽频带的反演结果。数值模拟试验表明:基于分形先验的非线性反演结果与理论模型吻合较好,实际资料的应用效果也证明了该反演方法的有效性。     

Solving multicollinearity in dam regression model using TSVD

Targeting the multicollinearity problem in dam statistical model and error perturbations resulting from the monitoring process,we built a regularized regression model using Truncated Singular Value Decomposition(TSVD).An earth-rock dam in China is presented and discussed as an example.The analysis consists of three steps:multicollinearity detection,regularization pa-rameter selection,and crack opening modeling and forecasting.Generalized Cross-Validation(GCV) function and L-curve criterion are both adopted in the regularization parameter selection.Partial Least-Squares Regression(PLSR) and stepwise regression are also included for comparison.The result indicates the TSVD can promisingly solve the multicollinearity problem of dam regression models.However,no general rules are available to make a decision when TSVD is superior to stepwise regression and PLSR due to the regularization parameter-choice problem.Both fitting accuracy and coefficients’ reasonability should be considered when evaluating the model reliability.     

各向异性正则化的多帧遥感图像盲复原算法

在大气湍流较强时,一般的遥感图像复原算法难以取得较好的复原效果。针对这种情况,提出了一种基于各向异性约束的多帧遥感图像盲复原算法。该算法不需要成像过程的先验信息,仅根据图像及点扩散函数的非负约束和支持域约束,即可得到较好的复原结果;同时该算法能够自适应地调整正则化参数,在实现图像复原的同时,保持边缘并抑制噪声。试验结果验证了该算法的良好性能,复原后图像的质量得到较大提高。     

Load or concentration,logged or unlogged? Addressing ten years of uncertainty in neural network suspended sediment prediction

This paper addresses current inconsistencies in methodological approaches for neural network modelling of suspended sediment. An expansion in the number of case studies being published over the last decade has yet to result in agreed guidelines on whether suspended sediment load or concentration should be modelled, and whether log‐transformation of data is either necessary or potentially beneficial. This contrasts with the well‐recognized guidelines that direct traditional sediment rating curve studies. The paper reports a comprehensive set of single‐input single‐output neural network suspended sediment modelling experiments performed on two catchments in Puerto Rico. It examines the impact of internal complexity, input variable choice and data transformation on the form, consistency and physical rationality of model outputs, the existence of localized overfitting and the usefulness of global performance metrics. Sound guidance on whether to model sediment load or concentration, and whether to model log‐transformed data is provided. Copyright © 2011 John Wiley & Sons, Ltd.     

Estimating Synaphobranchus kaupii densities: Contribution of fish behaviour to differences between bait experiments and visual strip transects

Kaup's arrowtooth eel Synaphobranchus kaupii is a small-bodied fish and an abundant inhabitant of the European continental slope. To estimate its local density video information using the remotely operated vehicle (ROV) Victor 6000 were collected at three locations in the Bay of Biscay slope. Two methods for estimating local densities were tested: strip transect counts and bait experiments. For bait experiments three behaviour types were observed in about equal proportions for individuals arriving near the seafloor: moving up the current towards the ROV, moving across the current and drifting with the current. Visible attraction towards the bait was the highest for individuals swimming against the current (80%) and about equally low for the other two types (around 30%); it did not depend on current speed nor temperature. Three main innovations were introduced for estimating population densities from bait experiments: (i) inclusion of an additional behaviour category—that of passively drifting individuals, (ii) inclusion of reaction behaviour for actively swimming individuals and (iii) a hierarchical Bayesian estimation framework. The results indicated that about half of individuals were foraging actively of which less than one third reacted on encountering the bait plume and the other half were drifting with the current. Taking account of drifting individuals and the reaction probability made density estimates from bait experiments and strip transects more similar.     

Latitudinal and altitudinal patterns of the endemic cacti from the Atacama desert to Mediterranean Chile

In this study we describe the biogeographic patterns of the endemic cacti from the Atacama Desert to the Mediterranean area of Chile. Our goals were: (1) to identify areas of high endemism, (2) to test Rapoport’s rule, (3) to test the geometric constraints hypothesis, (4) to explore temperature and precipitation as explanatory variables of species richness. We used a list of 72 species of cacti, ranging from 18° to 36° S and from 0 to 4500 m.a.s.l. A Bayesian analysis of Endemicity (BAE) was used to evaluate hierarchical relationships of endemism between different latitudinal bands. Rapoport’s rule was evaluated by examining the relationships between latitudinal/altitudinal mid-point, latitudinal/altitudinal range extent and species richness. The geometric constraints hypothesis was tested by examining the existence of mid-domain effect. The BAE indicated two areas of endemism: (1) the northern area between 18° S and 26° S, and (2) the southern area between 27° S and 36° S. The shape of the latitudinal gradient is non-linear, supporting the geometric constraints hypothesis. Altitudinal patterns, however, support Rapoport’s rule; a peak of endemism was found at low altitudes. The explanatory variables were elevation, minimum temperature of the coldest month, mean temperature of wettest quarter and annual precipitation.     

中国大地测量数据处理进展

本文介绍了近四年来中国学者在大地测量数据处理方面的主要进展。重点讨论了抗差估计、粗差探测与可靠性理论、病态条件诊断与正则化、半参数回归与非线性估计等方面的发展。     

CPT-based probabilistic evaluation of seismic soil liquefaction potential using multi-gene genetic programming

In this paper, liquefaction potential of soil is evaluated within a probabilistic framework based on the post-liquefaction cone penetration test (CPT) data using an evolutionary artificial intelligence technique, multi-gene genetic programming (MGGP). Based on the developed limit state function using MGGP, a relationship is given between probability of liquefaction (P_L) and factor of safety against liquefaction using Bayesian theory. This Bayesian mapping function is further used to develop a P_L-based design chart for evaluation of liquefaction potential of soil. Using an independent database of 200 cases, the efficacy of the present MGGP-based probabilistic method is compared with that of the available probabilistic methods based on artificial neural network (ANN) and statistical methods. The proposed method is found to be more efficient in terms of rate of successful prediction of liquefaction and non-liquefaction cases, in three different ranges of P_L values compared to ANN and statistical methods.