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31.
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
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Pierre Hudon In-Ho Jung Don R. Baker 《Physics of the Earth and Planetary Interiors》2002,130(3-4):159-174
Melting relations of β-quartz were experimentally determined at 1.0 GPa (1900±20 °C), 1.5 GPa (2033±20 °C), and 2.0 GPa (2145±20 °C) using a new high-pressure assembly in a piston–cylinder apparatus and substantial differences were found with data previously reported. The new melting data of β-quartz were combined and optimized with all available thermodynamic, volumetric, and phase equilibria data for β-cristobalite, β-quartz and coesite to produce a P–T liquidus diagram for silica valid up to 6.0 GPa. Using the new optimized thermodynamic parameters, the invariant point β-cristobalite+β-quartz+liquid and β-quartz+coesite+liquid were determined to lie at 1687±17 °C and 0.457 GPa, and 2425±25 °C and 5.00 GPa, respectively. 相似文献
34.
海洋平台结构振动的AMD主动控制参数优化分析 总被引:5,自引:0,他引:5
本文针对海洋平台结构的冰激振动和地震反应控制问题,提出了采用AMD主动控制的控制策略,结合JZ20-2MUQ平台结构进行了AMD控制系统的硬参数和软参数的优化分析,并就相应于最优参数下的AMD控制海洋平台结构冰激振动和地震反应的几种代表性工况进行了时程分析,得到了一些定性和定量的结论,为实际工程的控制设计提供了基础。本文提出的AMD主动控制方法对类似的海洋平台结构的控制问题也有参考价值。 相似文献
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The probability of crane living in reedy wetlands can reach 100%, at the same time, the area of reed, the water level and adjacent water area are main factors which control the crane's habitat selection. We all know that all these factors are spatially heterogeneous. For the Xianghai wetland safety and to protect the Xianghai wetland habitat of crane, this paper has mainly identified a solution to these problems. The wetland information is extracted from the TM images, which reflect the whole wetland landscape and are very important for both quantitative analysis of remote sensing observation of the earth system and positioning analysis in GIS database that is automatically extracted from DEM. The DEM for Xianghai characteristics of topography is created. On the basis of the GRID SUBMODULE, applying the GIS spatial overlay analysis, the relationship between the water level and the reed area below the water level and the rating distribution maps of reed area above water level is established. When the water level reaches the altitude of 165 m, the reed area, 981.2 ha is maximum, i.e., the water level of 165 m is the optimal. 相似文献
39.
灰色GM(1,1)模型最优维数的研究 总被引:2,自引:1,他引:2
灰色GM(1,1)模型的维数对模型的预测精度有很大的影响,本文通过自编的FORTRAN程序,在合适的范围内对GM(1,1)模型的维数进行自动优化,通过对宁波市地面沉降数据的计算分析,得到了C和P的定性关系,确定了优化的评价标准,维数最优化后的模型能反映预测数列变化幅度的大小。 相似文献
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