胶莱盆地南部大盛群、王氏群的划分与对比

胶莱盆地在胶东半岛地质构造及造山带研究中占有重要地位,其巨厚的白垩系陆相沉积是石油系统多年的研究目标。胶莱盆地南部白垩纪的岩石地层序列较其北部更为复杂,其认识几经反复,其中尤以大盛群与王氏群和莱阳群的部分单位的关系为甚。本次工作通过详细对比其沉积层序、相互关系、古生物组合、岩石学特征及同位素年龄等因素,认为大盛群与王氏群属同一沉积层序,沉积基底相同、沉积环境相似、古生物群落时代一致,二者具有同时代、同沉积相、同岩石组合的一致性,应是一套地层,建议今后使用统一地层名称。     

内插法在相关干涉仪测向体制中的应用

测向误差的减小一直以来都是无线电测向精度提高的一个难点,对于不同的测向体制所采用的减小测向误差的方法都不尽相同。本文主要介绍的是相关干涉仪测向体制的基本原理以及通过内插法的应用来减小测向误差的方法。     

相关条件下基于N-P准则的分布式检测理论研究

本文针对并行网络、二元局部判决的情况,研究了在相关条件下基于N-P准则的分布式检测融合算法,给出了在联合概率密度已知和未知两种情况下的最优融合规则的理论推导及相应的解决方案,并在实验仿真的基础上,得到了部分有益的结论。     

以一种新的距离度量作为反馈的相关跟踪方法

基于相关的模板匹配方法在图像跟踪中得到了广泛的应用,但是这种方法的主要缺点是对图像噪声非常敏感,而且由这种方法得出的相关曲面比较平坦。为了有效抑制噪声和局部遮挡对图像的影响,提出用鲁棒统计中的一个值代替相关值作为距离度量。它不是计算两幅图像的对应像素差值,而是计算两幅图像中差别不大的对应像素对的个数。实验证明这样得到的曲面相对　　收稿日期:2003 08 31;　修订日期:2003 10 28作者简介:张桂林(1944 ),男,天津人,教授,博士生导师,主要研究方向为自动识别、人体生物统计特征识别、图像处理算法与系统性能评估等。　　　　　　　要尖锐得多。当上述的距离度量应用于跟踪过程中时,模板的合理更新对跟踪非常重要。基于上述的距离度量方法,提出了一种新的模板更新策略。利用两幅图像中近似像素在整修匹配模板像素中所占的比例大小决定加权系数。这种加权策略可以自适应地根据图像序列的变化选择更新相关模板,同时在一定程度上减小模板漂移的危险。     

一类广义几何序列的相关函数

计算序列的周期相关函数是一个很困难但又十分重要的问题。本文首次给出了线性相关广义几何序列的相关函数，从而部分地解决了Ｋｌａｐｐｅｒ提出的相关函数计算问题。     

APPLICATION OF GRAY SYSTEM THEORY IN SBS MODIFIED ASPHALT

A system whose partial information is known and partial information is unknown is called gray system. In this paper, the compatibility relationship between Styrene-Butadiene-Styrene (SBS) modifier and base asphalt composition was studied by correlation analysis method. The analysis results of correlation level show that aromatics and asphaltene of base asphalt affect SBS modified effect mainly as the content of SBS is lower, while the content of aromatics and resin become the main effect factors as SBS content is increased.     

寒区沥青胶浆延性研究

首交提出了沥青胶浆延工的概念，并测定、分析了两种寒区沥青、四种粉胶比在四个温度下的沥青胶浆延度。认为沥青胶浆延度较沥青延度更能反映沥青混合料的流变性能，而且胶浆延度与温度、粉胶比之间有很好的相关性。     

大麻工艺纤维长度与细度的相关性初探

通过对大麻工艺纤维长度和直径投影宽度的相关性研究，认为大麻工艺纤维长度和细度之间存在“越长越粗，越短越细”的规律。     

Modeling of Temperature–Frequency Correlation Using Combined Principal Component Analysis and Support Vector Regression Technique

A good understanding of environmental effects on structural modal properties is essential for reliable performance of vibration-based damage diagnosis methods. In this paper, a method of combining principal component analysis (PCA) and support vector regression (SVR) technique is proposed for modeling temperature-caused variability of modal frequencies for structures instrumented with long-term monitoring systems. PCA is first applied to extract principal components from the measured temperatures for dimensionality reduction. The predominant feature vectors in conjunction with the measured modal frequencies are then fed into a support vector algorithm to formulate regression models that may take into account thermal inertia effect. The research is focused on proper selection of the hyperparameters to obtain SVR models with good generalization performance. A grid search method with cross validation and a heuristic method are utilized for determining the optimal values of SVR hyperparameters. The proposed method is compared with the method directly using measurement data to train SVR models and the multivariate linear regression (MLR) method through the use of long-term measurement data from a cable-stayed bridge. It is shown that PCA-compressed features make the training and validation of SVR models more efficient in both model accuracy and computational costs, and the formulated SVR model performs much better than the MLR model in generalization performance. When continuously measured data is available, the SVR model formulated taking into account thermal inertia effect can achieve more accurate prediction than that without considering thermal inertia effect.     

Efficient Spreadsheet Algorithm for First-Order Reliability Method

A new spreadsheet-cell-object-oriented algorithm for the first-order reliability method is proposed and illustrated for cases with correlated nonnormals and explicit and implicit performance functions. The new approach differs from the writers earlier algorithm by obviating the need for computations of equivalent normal means and equivalent normal standard deviations. It obtains the solution faster and is more efficient, robust, and succinct. Other advantages include ease of initialization prior to constrained optimization, ease of randomization of initial values for checking robustness, and fewer required optimization constraints during spreadsheet-automated search for the design point. Two cases with implicit performance functions, namely an asymmetrically loaded beam on Winkler medium and a strut with complex supports are analyzed using the new approach and discussed. Comparisons are also made between the proposed approach and that based on Rosenblatt transformation.