半参数平差模型估计量的精度评定

将半参数估计理论引入测量数据处理理论中,利用Blight和Ott提出的思想,用多项式函数来表示半参数平差模型中的非参数分量,从而得到了半参数平差模型中参数分量和非参数分量的Bayes估计量,通过理论证明,半参数模型参数分量的Bayes估计为通常意义下高斯马尔可夫模型参数估计值与参数期望的加权平均,是一致、渐近无偏和渐近有效估计量,并且其方差小于参数模型中参数估计量的方差。在一定情况下推广了平差理论,具有一定的理论价值。     

构建基于GIS的房产管理

阐述了基于GIS房产管理的关键是建立统一的数据分类与编码标准,核心是建立房屋的空间地理属性信息、自然属性信息、社会人文属性信息的链接,基础是建立房产地理信息数据库。并提出了建立房产地理信息数据库的方法、设计思路和方式。     

1∶500,1∶1000,1∶2000系列数字化测绘产品的精度目标与实现

1∶500,1∶1000,1∶2000系列数字化测绘产品按其生产工艺和用途的不同其精度规格也不尽相同,但产品的精度状况始终是测绘生产部门与用户所关心的问题。本文列举了现行有关规范的相关精度指标、规格,并结合产品的用途、特点和测绘生产的实际,简要阐述精度目标的控制与实现过程,对测绘实际工作有一定的参考价值。     

追忆李四光对防震减灾的贡献,以系统整体观指导防震应急

笔者在追忆李四光地震科学和防震减灾指导思想的基础上,提出了以系统整体观指导防震应急的新论点,包括:运用地壳运动整体观研究地震规律;应用地震预测整体观进行地震预测;划分活动性构造体系,研究构造活动性;加强综合监测,研究各种地震前兆和相关的自然变异的发展趋势;圈定地震风险区,制定防震应急预案等.并结合中国的实际情况进行了论述.     

QuickBird影像制作1：10000DOM方法探讨

随着卫星遥感影像数据更加广泛地应用于测绘,针对QuickBird影像制作1：10000 DOM的方法,从正射纠正的三种不同方式进行了实验和探讨,分析了利用外业控制点或者在原有DRG、DOM上选取控制点制作DOM的方法、精度、工作量,总结提出了方便、快捷、实用的工作模式。     

基于免疫粒子群优化算法的影像纹理分类

粒子群优化算法是基于群智能的随机全局优化方法,它源于对鸟群简化社会系统的模拟。为了提高标准粒子群优化算法的收敛性能,将生物免疫系统的记忆能力和多样性引入标准粒子群优化算法,提出一种免疫粒子群优化算法。在提取纹理样本Laws纹理能量模板特征、小波特征等纹理特征的基础上,提出针对分类问题的粒子表达方法和群体寻优策略,实现了基于免疫粒子群算法的纹理分类。实验结果表明,与标准粒子群优化算法相比,免疫粒子群优化算法在获取训练样本类别中心时具有较好的收敛性能,并且基于该算法的影像纹理分类具有较高的分类精度。     

Automatic classification of volcanic earthquakes by using Multi-Layered neural networks

The application of neural networks as classifiers of seismic events is described with the aim of developing an automatic system for the classification of explosion quakes at the Stromboli volcano. The architecture of the network that we trained to identify four different classes of shocks was a Multi-Layer Perceptron, using the Back Error Propagation algorithm. Five different approaches for representing the information embedded in the seismograms, both in the time and in the frequency domain, were considered, and the results compared. The direct use of the time series of the shocks was not satisfactory. The auto-correlation function worked well, but in some cases it was misleading. A better performance was obtained with a frequency domain representation. Finally, the use of the envelope function did not work well. Combining parameters such as the auto-correlation and envelope functions can improve one source of error, but it may introduce new ones. The performance obtained highlights the importance of the data attributes used for the training of the network. Topologies with eight neurons in a single hidden layer gave, on average, the best results among the considered neural network structures. The overall results provide a large number of events (89% with the best performance) correctly classified, indicating that this automatic technique is reliable, and encouraging further applications in the field of volcanic seismology.     

论Eppley PIR精密红外辐射仪的测量精度

本文依据红外辐射表(PIR)的结构、性能和工作原理讨论了测量精度及有关影响因素,比较了粗测和精测两种方法的特点,在此基础上提出了各测量方法的适用范围和精度范围以及提高测量精度的措施,同时也给出了一些特定场合下的测量实例及提高测量精度的具体方法。分析表明:精测方法具有很好的测量精度以及很强的环境适应性。粗测在限定的温度范围内具有测量简单、换算方便、易于实现自动化等优点,精度尚能满足一般要求,但在限定的温度范围以外,测量精度急剧恶化。在影响测量精度的各因素中以温度响应中表体热辐射测量的影响最大,在粗测方法中表内电池的性能与测量精度关系重大。强烈日射对测量精度有一定影响,经订正后可基本消除。     

Engineering geological studies and tunnel support design at Sulakyurt dam site, Turkey

This paper presents the results of engineering geological investigations and tunnel support design studies, carried out at the Sulakyurt dam site, northeast of Ankara, Turkey. The Sulakyurt dam will be used for flow control and water storage for irrigation projects. Studies were carried out both in the field and the laboratory. Field studies include engineering geological mapping, intensive discontinuity surveying, core drilling and sampling for laboratory testing. The diversion tunnel will be driven in rock mass, consisting of granite and diorite. Empirical, analytical and numerical methods were combined for safe tunnel design. Rock mass rating (RMR), Rock mass quality (Q) and Geological strength index (GSI) systems were used for empirical rock mass quality determination, site characterization and support design. The convergence–confinement method was used as analytical method and software called Phase², a 2D finite element program, was utilized as numerical method. According to the results acquired from the empirical, analytical and numerical methods, tunnel stability problems were expected in both granite and diorite rock masses. The support system, suggested by empirical methods, was applied and the performance of suggested support system was evaluated by means of numerical modelling. It was concluded that the suggested support systems were adequate, since after applying the suggested support system to granite and diorite, tunnel deformation and the yielded elements around the tunnel decreased significantly. Thus, it is suggested that for more reliable support design empirical, numerical and analytical methods should be combined.     

Modeling of the classification behavior of the diaphragms used in multi-chamber cement mills

A new approach has been developed for describing the classification that arises at the diaphragm in multi-chamber ball mills. Fourteen industrial scale cement mills have been sampled in this study and after mass balancing, model fits of the equipment were done. Successive mill product predictions for the sampled conditions were achieved, and requirements to build up an optimization capable model are discussed.