浅层地震勘探资料处理中的速度分析参数选取

浅层人工地震勘探是当前城市地震活断层探测的主要方法,勘探精度不仅受激发、接收等因素的影响,还与地震数据处理的精度密切相关。速度分析是地震勘探资料处理中的关键环节,它的准确与否对动校正、共深度点叠加、叠后偏移及时深转换等都将产生影响。针对浅层地震资料目的层较浅、叠加次数少和城市背景干扰大等特点,文中对速度分析的参数选取问题进行了研究。首先通过对相邻CDP道集内各接收道炮检距的分析,以及单个和多个CDP道集的对比,提出了用于速度分析的CDP大道集的抽取原则。并通过对不同的CDP大道集、速度扫描间隔、计算时窗长度、动校切除比例等所获得的速度谱的对比分析,对速度谱扫描过程中各参数的选取提出了建议,并对速度分析及时深转换过程中值得注意的问题进行了讨论     

Population dynamics of cryptogenic calcarean sponges (Porifera,Calcarea) in Southeastern Brazil

The calcarean sponge Paraleucilla magna is classified as being an invasive species on the Mediterranean Sea, where it causes economic damages to mollusc farms. On the Brazilian coast, this species is considered to be cryptogenic, and information on its ecology is scarce. The same is true for Sycettusa hastifera, another calcarean sponge with a worldwide distribution. Data on the ecology of these species could help in elucidating their potential to become a threat if they are found to be exotic species in Brazil. In the present work, we studied habitat selection, growth and mortality of early juveniles of P. magna and habitat selection of S. hastifera in a Marine Reserve from Southeastern Brazil, where these species are abundant in the benthic community. Granite plates were used for habitat selection analysis, varying in substrate inclination (vertical and horizontal) and exposure to light and hydrodynamism (exposed and sheltered). To analyse the growth and mortality rates, sponges were mapped and then measured once a week for 10 weeks. If a monitored sponge was not found in the following week, it was considered to be dead. Our results showed that, although P. magna and S. hastifera are capable of inhabiting substrates exposed to different environmental conditions, they showed habitat preferences. Growth of the juveniles of P. magna seemed not to have damaged any neighbouring invertebrates. The mortality of juveniles of this species was higher during the first 2 weeks of life but its causes could not be elucidated.     

成像光谱数据特征选择及小麦品种识别实验研究

针对河北栾城获得的MAIS成像光谱仪数据用于小麦品种识别进行了特征选择和分类研究。利用遗传算法以JM距离为准则并结合实验区小麦的生物物理特性，进行了最佳波段选择；利用Fuzzy—Anmap分类器及选出的最佳波段对成像光谱数据进行了分类，区分出了4种小麦品种，小麦的总体分类精度超过97％。     

Variogram Model Selection via Nonparametric Derivative Estimation

Before optimal linear prediction can be performed on spatial data sets, the variogram is usually estimated at various lags and a parametric model is fitted to those estimates. Apart from possible a priori knowledge about the process and the user's subjectivity, there is no standard methodology for choosing among valid variogram models like the spherical or the exponential ones. This paper discusses the nonparametric estimation of the variogram and its derivative, based on the spectral representation of positive definite functions. The use of the estimated derivative to help choose among valid parametric variogram models is presented. Once a model is selected, its parameters can be estimated—for example, by generalized least squares. A small simulation study is performed that demonstrates the usefulness of estimating the derivative to help model selection and illustrates the issue of aliasing. MATLAB software for nonparametric variogram derivative estimation is available at http://www-math.mit.edu/~gorsich/derivative.html. An application to the Walker Lake data set is also presented.     

结合引力场理论的道路自动选取方法

针对复杂网络模型被广泛应用于道路选取的研究中,少有方法顾及道路网对偶图中多级邻居节点的影响,导致对道路的重要性评价缺乏准确性和可靠性的问题。该文将道路网对偶图节点的结构特征值视作质量,将节点间的最短距离视作距离,结合引力场方程实现道路自动选取,较好地将道路网对偶图中多级邻居节点的影响纳入到道路重要性的计算中,从而实现对道路重要性的准确评估。通过对兰州市城关区的路网进行实验,结果表明本文方法所选取的路网较好地保持了原始道路网的整体结构、覆盖范围、密度分布、拓扑特征和连通性。     

Modeling of environmental influence in structural health assessment for reinforced concrete buildings

One branch of structural health monitoring (SHM) utilizes dynamic response measurements to assess the structural integrity of civil infrastructures. In particular,modal frequency is a widely adopted indicator for structural damage since its square is proportional to structural stiffness. However,it has been demonstrated in various SHM projects that this indicator is substantially affected by fluctuating environmental conditions. In order to provide reliable and consistent information on the health status of the monitored structures,it is necessary to develop a method to filter this interference. This study attempts to model and quantify the environmental influence on the modal frequencies of reinforced concrete buildings. Daily structural response measurements of a twenty-two story reinforced concrete building were collected and analyzed over a one-year period. The Bayesian spectral density approach was utilized to identify the modal frequencies of this building and it was clearly seen that the temperature and humidity fluctuation induced notable variations. A mathematical model was developed to quantify the environmental effects and model complexity was taken into consideration. Based on a Timoshenko beam model,the full model class was constructed and other reduced-order model class candidates were obtained. Then,the Bayesian modal class selection approach was employed to select the one with the most suitable complexity. The proposed model successfully characterizes the environmental influence on the modal frequencies. Furthermore,the estimated uncertainty of the model parameters allows for assessment of the reliability of the prediction. This study not only improves the understanding about the monitored structure,but also establishes a systematic approach for reliable health assessment of reinforced concrete buildings.     

中国煤层气选区评价标准探讨

煤层气选区评价关系到勘探的成功与否,是煤层气勘探研究最基础的工作。近年国内外煤层气成藏理论、开发技术的快速发展,使得低煤阶气藏、连续薄层气藏、高煤阶低渗气藏等都获得成功开发,大大拓宽了煤层气的开发领域。此前国内在中煤阶成藏优势论基础上建立的选区标准已不适合当前的要求。根据当前存在的问题,结合煤层气成藏类型、地质特点和技术现状,对中国煤层气勘探选区评价标准进行了研究,试图建立一套煤层气选区评价标准,以期对国内煤层气选区评价工作提供借鉴。     

中国南极中山锚地勘测

本文介绍了南极中山锚地的选择条件,勘测实施过程及水文、气象特点,并对测量区域作了分析研究与评价,科学地确定了适合科考船抛锚的锚地,致使“雪龙”船首次在中山锚地抛锚试抛成功,结束了中山站附近海域无锚地的历史。     

一种多/高光谱遥感图像端元提取的凸锥分析算法

凸锥分析方法常用于多光谱和高光谱遥感图像的端元提取。遥感图像中的每个像元都可以看作一个多维向量,整幅影像看作由离散的非负向量构成的凸锥,通过寻找凸锥的角点来自动获取图像的端元。本文提出了一种自动选择最佳凸锥角点的方法,应用到传统的凸锥分析方法中,提高了凸锥分析方法的效率。利用模拟数据和真实数据实验验证了算法的可行性。     

基于特征选取及广义傅立叶分形的SAR图像海洋溢油检测算法

针对海上溢油SAR图像中油膜与类油膜的识别问题,提出了一种结合傅立叶分形与特征提取的检测算法。由于分形特征可以具有无穷多的细节,并在不同的研究尺度存在自仿射特性。这与油膜及类油膜表面的几何形貌特征非常吻合。该算法通过计算样本的傅立叶分形特征,组成油膜与类油膜的特征空间。然后,应用基于差分进化的特征选取方法将利于分类的重要特征值筛选出来。再利用重要特征值对原有样本进行分类。实验表明,经特征选取的分形特征向量能够以100%的准确率将两类样本区分开。该算法在选取重要特征的同时实现了对高维特征空间降维的目的,该思想可以应用于其他的基于高维特征的识别系统中,具有普遍的适用性。