资源量估算的边界分析与矿化体圈定

资源量估算总是在特定的估算域中进行,其边界条件对估值结果有着显著的影响。传统方法采取用工业指标来圈定矿体并进行资源量估算的硬边界条件,过于强调了矿床的经济性,而对矿床的地质和地质统计学规律重视不够。本文介绍了国际上流行的资源量估算域的相关概念及边界分析方法,并通过实际案例来探讨其在资源量估算中的应用,在此基础上提出了利用三维软件进行矿(化)体圈定的基本原则。实践表明,利用软边界约束或圈定矿化体进行品位估计,可能更符合勘查阶段资源量估算的要求,进而降低估算域边界的不确定性带来的估值风险。     

多视影像相对方位关系误判检测的置信传播算法

场景模糊或者不同场景中的重复纹理会导致影像匹配时产生大量的误匹配点,从而得到误判的相对方位关系。本文引入概率推论方法,提出了一种改进的误判相对方位关系检测算法,利用回路闭合约束构建了基于影像间相对方位关系的贝叶斯网络,推导了贝叶斯网络中的先验概率模型,并利用置信传播算法解算了贝叶斯网络中最大后验概率的求解问题。试验结果表明,利用本文提出的全局一致性约束方法可以有效检测影像间误判的相对方位关系,改善场景重建的结果,并且具有很高的计算效率。     

基于菱形计盒分维估值计算的水深综合方法

文中提出一种基于菱形计盒分维估值计算的二倍数水深综合方法,对水深点群进行以菱形尺度单元进行分形计算,验证可行性;利用分维值确定目标比例尺下单位尺度内的压缩比,从而确定保留点数。该方法可以应用于快速确定综合目标点数,提高水深选取效率,且构建的菱形网可作为水深综合的参考网。     

一种虚拟空间划分的室内指纹库定位方法

RSSI测量距离技术被广泛应用于距离定位的领域。针对传统的Zigbee指纹定位算法和复杂环境,文章提出了一种虚拟空间划分的Zigbee指纹库定位算法,其中包括虚拟空间划分最邻近定位算法、虚拟空间划分加权最邻近定位算法和虚拟空间划分贝叶斯定位算法。实验结果表明,在最优情况下,此方法能将定位误差抑制在1.50m。     

理解大气资料同化的根本概念

本文阐明随机变量是大气资料同化的根本概念。其根本性可以体现在两个方面：(1) 原理上,大气资料同化的科学实质是建立在随机变量这个概念上。由于将资料同化的可用信息视为随机变量的数据,所以概率论与数理统计学成为资料同化的数学基础,使得资料同化有了基于估计理论的最优标准及其数学形式,成为一门科学。(2) 实施上,基于随机变量这个概念下的数据是理解大气资料同化发展史的钥匙。由于资料同化的具体实施表现为各种同化方法中可用信息的资料融合,将资料同化的可用信息视为随机变量的数据,可以清晰地揭示主流同化方法的发展进程对应着其可用信息在内涵和种类上的不断扩展,这个扩展具体地体现了同化发展史的一个循序渐进的内在发展逻辑。     

THE DESIGN AND CORRECTION OF A QUANTITATIVE METHOD OF SNOW ESTIMATE BY RADAR

An optimization method is based to design a snowfall estimate method by radar for operational snow warning, and error estimation is analyzed through a case of heavy snow on March 4, 2007. Three modified schemes are developed for errors caused by temperature changes, snowflake terminal velocity, the distance from the radar and calculation methods. Due to the improvements, the correlation coefficient between the estimated snowfall and the observation is 0.66(exceeding the 99% confidence level), the average relative error is reduced to 48.74%, and the method is able to estimate weak snowfall of 0.3 mm/h and heavy snowfall above 5 mm/h. The correlation coefficient is0.82 between the estimated snowfall from the stations 50 to 100 km from the radar and the observation. The improved effect is weak when the influence of the snowflake terminal velocity is considered in those three improvement programs, which may be related to the uniform echo. The radar estimate of snow, which is classified by the distance between the sample and the radar, has the most obvious effect: it can not only increase the degree of similarity, but also reduce the overestimate and the undervaluation of the error caused by the distance between the sample and the radar.The improved algorithm further improves the accuracy of the estimate. The average relative errors are 31% and 27% for the heavy snowfall of 1.6 to 2.5 mm/h and above 2.6 mm/h, respectively, but the radar overestimates the snowfall under1.5 mm/h and underestimates the snowfall above 2.6 mm/h. Radar echo may not be sensitive to the intensity of snowfall, and the consistency shown by the error can be exploited to revise and improve the estimation accuracy of snow forecast in the operational work.     

半参数模型稳健估计及其应用

在半参数模型估计中,均假设观测误差服从正态分布.当观测量含有粗差时,粗差对参数和非参数估计的影响是不可忽略.基于此,首先在总结线性参数模型稳健估计基本理论的基础上,论述了M估计权因子的确定方法.然后提出了半参数模型稳健估计方法,并导出半参数模型(广义)补偿最小二乘稳健估计的基本公式.最后通过两个模拟算例验证了其估计方法的有效性.     

用模糊方法评价摆式波力电站的性能设计问题

本文通过对模糊方法,对模型试验的数据进行分析,提出并解决了摆式波力电站中设计因素的优先级问题,给出了摆式波力电站各主要设计因素的隶属度,提出了摆式波力电站的模糊评价方法,最后给出了模糊综合评价的两种途径。     

一种基于统计模型的自适应窗口匹配方法

提高匹配精度和效率是摄影测量的主要研究内容之一。本文基于统计模型计算窗口灰度波动及视差波动,根据视差和其不确定性估计调整窗口。在调整窗口的同时确定最佳匹配点位,实现动态窗口匹配,匹配精度达到子像素级。通过对无人机影像匹配的实验结果验证了模型的有效性和实用性。     

Informal likelihood measures in model assessment: Theoretic development and investigation

Within hydrology performance criteria such as the Nash–Sutcliffe efficiency have been used to condition the parameter space of a model. Their use is motivated by the fact that the stochastic error series between a model output and corresponding observations is the result of the composite effect of multiple error sources which cannot be described, even in form, a priori. This paper formalises the use of such performance criteria within a Bayesian framework, such as Generalised Likelihood Uncertainty Estimation (GLUE), by introducing the concept of Informal Likelihoods. Informal Likelihoods are used to characterise desirable features in the relationship between the model output and corresponding observed data. A number of common performance criteria are considered as Informal Likelihoods. Analytical results and a simulation indicate all of the performance criteria considered as Informal Likelihoods in this paper have one or more properties which may be considered undesirable, but may perform no less well in conditioning model parameters than formal likelihoods for which the assumptions are only mildly incorrect.