A review and analyses of plumb-line calibration     

José L.  Lerma  Miriam  Cabrelles 《The Photogrammetric Record》2007,22(118):135-150

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星载加速度计的动力法校准   总被引：1，自引：0，他引：1  

邹贤才  李建成  罗佳  徐新禹 《武汉大学学报(信息科学版)》2007,32(12):1152-1155

通过模拟轨道，利用动力法对星载加速度计校准进行了研究。用不同参考重力场模型获得的校准参数分别重新积分卫星轨道，与模拟轨道的差异最大可达m级。结果表明，参考重力场模型误差对加速度计校准的影响不可忽略，在校准加速度计的同时应解算重力场模型，以削弱模型误差的影响。  相似文献   

A cellular automata model of surface water flow   总被引：1，自引：0，他引：1  

Jay A. Parsons  Mark A. Fonstad 《水文研究》2007,21(16):2189-2195

Previous cellular automata models of surface water flow have been constructed to reflect steady, gradually‐varied flow conditions. While these models are extremely important in showing the near‐equilibrium forms that result from the interactions of water and boundary material, highly dynamic forms and processes require models that represent unsteady flow conditions. In order to simulate unsteady flow in a cellular model of surface water flow, the conservation of mass and the Manning's equations are coupled with an algorithm to delay the movement of water from one pixel to the next until the correct timing is reached. This approach yields highly realistic flood wave hydrographs when compared with flood observations in the Walnut Gulch Experiment Watershed. Coupling this unsteady flow model with simple laws of sediment erosion, transport, and deposition should allow event‐based simulations of watershed and river channel geomorphologic change. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

电子经纬仪测量系统在偏置型抛物面天线检测中的应用     

李广云  黄玲 《测绘工程》1998,7(4):27-31,37

将电子经纬仪工业测量系统模拟摄影测量系统,把经纬仪水平角、垂直角观测值化算为虚拟像点坐标观测值,按摄影测量光束法平差进行二台或多台经纬仪间的系统定代间坐标解算,从而实现了经纬仪在任意姿态下的空间坐标测量功能。在光束法平差的基础上开发了中文版ＴＳＳＴ２．００工业测量系统软件。最后介绍了偏置型抛物面天线的数学模型和ＴＳＳＴ工业测量系统在其检测中的应用。  相似文献   

Modelling dispersion in complex open channel flows: Fuzzy calibration (2)     

B. G. Hankin  K. J. Beven 《Stochastic Environmental Research and Risk Assessment (SERRA)》1998,12(6):397-412

Part 1 of this study assessed the effectiveness of dispersion models based around random particle tracking (RPT) applied an overbank flow in the Flood Channel Facility at HR Wallingford. Several of the RPT models that were used predicted the mixing behaviour of the tracer in the complex channel flow to within an acceptable accuracy. If there is no uniqueness in the model structure which can be used to represent the true system to within the limitations of the available observations, then this implies an inherent degree of ambiguity in our knowledge of the physically based model structure. This suggests that we should be less forthright in the optimisation of each individual model structure, and perhaps investigate more of the parameter combinations for each model which yield feasible simulations of the system. An alternative fuzzy calibration technique is introduced which avoids the optimisation process and takes account of uncertainties in the model structure, parameter sets and observed data in prediction.  相似文献   

水氡仪的标定与故障分析     

张贵运  庞云峰 《山西地震》1998,(2):58-60

在多年工作的基础上,介绍了水氡仪器的标定方法,分析了水氡仪器常见故障的原因及判别、排除方法等,指出所介绍的方法可供仪器标定人员工作时参考。  相似文献   

机载成像光谱仪的外定标方法          下载免费PDF全文

张玉香  张广顺 《应用气象学报》1998,9(4):485-491

该文描述了基于反射率方法的机载中分辨率成像光谱仪（AMODIS）外定标方法。可见光和近红外波段的17个通道定标结果表明,成像光谱仪两个飞行高度测值的外定标系数是非常吻合的,其相对差为0.19%～3.89%;成像光谱仪关于草地航测的反演值与地面实测值比较,结果也是比较接近的。  相似文献   

Continuous spatially distributed simulation of surface and subsurface hydrological processes in a small semiarid catchment     

Marco Maneta  Susanne Schnabel  Victor Jetten 《水文研究》2008,22(13):2196-2214

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吕永清  蔡亚先 《大地测量与地球动力学》2007,27(5):119-122

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Prediction of uniaxial compression PFC3D model micro‐properties using artificial neural networks     

A. S. Tawadrous  D. DeGagné  M. Pierce  D. Mas Ivars 《国际地质力学数值与分析法杂志》2009,33(18):1953-1962

Artificial neural networks are used to predict the micro‐properties of particle flow code in three dimensions (PFC3D) models needed to reproduce macro‐properties of cylindrical rock samples in uniaxial compression tests. Data for the training and verification of the networks were obtained by running a large number of PFC3D models and observing the resulting macro‐properties. Four artificial networks based on two different architectures were used. The networks used different numbers of input parameters to predict the micro‐properties. Multi‐layer perceptron networks using Young's modulus, Poisson's ratio, uniaxial compressive strength, model particle resolution and the maximum‐to‐minimum particle ratio showed excellent performance in both training and verification. Adding one more variable—namely, minimum particle radius—showed degrading performance. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献