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81.
本文通过分析实验室风浪周期分布,发现风浪周期累积概率分布曲线低于Longuet-Higgins理论结果,在小概率周期区域实验结果与理论结果的差异明显。对实验结果进一步分析发现,在谱不是很窄时,在小概率处风浪周期累积概率随谱宽度的增大而降低,这与窄谱假定下的理论结果相反,Longuet-Higgins理论结果在小概率处不便于描述周期分布随谱宽度的变化。根据实验结果提出风浪周期的Weibull分布经验公式,Weibull分布中的参数依赖于谱宽度。 相似文献
82.
黄、东海海域水团发育对底质沉积物分布的影响 总被引:6,自引:0,他引:6
通过对黄、东海海域底质沉积物中的细粒级粘土矿物组合特征和全粒级碳酸盐含量分析、对比上覆水团和悬浮体资料,探讨研究区水团发育消长对底质沉积物分布的影响作用。结果表明研究区可以划分为长江冲淡水影响的长江型物质沉积区;黄海水影响的黄河型物质沉积区和黑潮水以及东海次表层水影响的残留型物质沉积区。而水团发育消长可直接影响下伏底质的分布特征。黄河型物质沉积区与残留型物质沉积区的分界相应于黄海冷水向东南扩展与黑潮次中层混合水向陆架爬升互为消长的长期综合平衡位置,而黄海冷水向东南的扩展范围代表着黄河物质在陆架向东南扩展沉积的最大范围. 相似文献
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高空间分辨率遥感影像中地物目标内部光谱信息复杂性的增强,使得传统基于光谱特征值的数据处理方法效果不再显著,影像分割为解决这一问题提供了一种思路,成为当前高空间分辨率遥感影像处理的研究焦点.时刻独立脉冲耦合神经网络具有状态相近、空间相邻神经元相互耦合同步脉冲激发和区域之间神经元脉冲激发时刻独立两大特点,已被应用于非遥感影像分割中,并取得较好效果.本文结合高空间分辨率遥感影像特点,通过对网络参数进行实验和分析,提出一个基于时刻独立脉冲耦合神经网络的高空间分辨率遥感影像分割方法,并利用空间分辨率0.3m的航空影像进行了数据试验,将分割结果进行讨论并与现有时刻独立脉冲耦合神经网络方法和ISODATA方法分割结果进行对比分析.结果表明:时刻独立脉冲耦合神经网络在高空间分辨率遥感影像分割处理中具有很好的应用前景. 相似文献
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LIU Luofu HUO Hong GUO Yongqiang CHEN Lixin LI Shuangwen ZHAO Yande LI Yan WANG Ping CHEN Zhijun 《中国地球化学学报》2008,27(1):1-8
The results presented in this paper indicated that the carbazole-type compounds have high thermal stability and also show stability in oxidation and bio-degradation. This kind of compounds still has high concentrations and a complete distribution in the analyzed dry asphalt samples, showing that they are particularly useful in the study of hydrocarbon migration of the paleo-pools. The difference in the contents of nitrogen compounds in the Silurian dry asphalts from the Awati, Tabei and Tazhong areas is attributed to the difference in the extent of oxidation and (or) bio-degradation for the areas; the Awati and Tabei areas underwent relatively strong oxidation and bio-degradation. During the first stage of hydrocarbon pool formation in the Silurian system in the Tazhong and Tabei areas of the Tarim Basin (at the end of the Silurian period) and at the second stage in the Awati area (in Permian), the hydrocarbons experienced a long-distance migration. 相似文献
88.
Xin Li Dongliang Wang Baoquan Liu Chunling Ren Jianying Guo Xuefeng Su Jian Wang 《中国地球化学学报》2008,27(4):412-419
The northern margin of the Qaidam Basin is one of the main oil-gas exploration areas in western China, where source rocks are composed mostly of Middle and Lower Jurassic dark mud shale, carbargillite and coal. A large number of subsurface and outcrop samples differing in lithology with different types of organic matter were selected for resource evaluation, research and calculation. And among them, 13 samples were used for simulation experiment on hydrocarbon generating potential of various source rocks. At first, two kinds of heating modes were compared through simulation experiment, including single temperature-step heating and continual heating. Perhaps, the process of hydrocarbon generation and expulsion occurred naturally between a close system and an open system. In addition, the first heating mode was convenient, and all its reaction products were involved in the whole thermal evolution, and the final simulation experimental results were basically in consistency with the natural evolution trend Therefore, the first heating mode was adopted and the hydrocarbon yield of every sample was worked out. According to the type and lithology of organic matter and the hydrocarbon yield of samples for simulation experiment, hydrocarbon generation and expulsion mode with three kinds of lithology and five types of source rock has been established to provide the basis for hydrocarbon generation evaluation, research and resource calculation. 相似文献
89.
A framework of region-based spatial relations for non-overlapping features and its application in object based image analysis 总被引:2,自引:0,他引:2
Yu Liu Qinghua Guo Maggi Kelly 《ISPRS Journal of Photogrammetry and Remote Sensing》2008,63(4):461-475
Object based image analysis (OBIA) is an approach increasingly used in classifying high spatial resolution remote sensing images. Object based image classifiers first segment an image into objects (or image segments), and then classify these objects based on their attributes and spatial relations. Numerous algorithms exist for the first step of the OBIA process, i.e. image segmentation. However, less research has been conducted on the object classification part of OBIA, in particular the spatial relations between objects that are commonly used to construct rules for classifying image objects and refining classification results. In this paper, we establish a context where objects are areal (not points or lines) and non-overlapping (we call this “single-valued” space), and propose a framework of binary spatial relations between segmented objects to aid in object classification. In this framework, scale-dependent “line-like objects” and “point-like objects” are identified from areal objects based on their shapes. Generally, disjoint and meet are the only two possible topological relations between two non-overlapping areal objects. However, a number of quasi- topological relations can be defined when the shapes of the objects involved are considered. Some of these relations are fuzzy and thus quantitatively defined. In addition, we define the concepts of line-like objects (e.g. roads) and point-like objects (e.g. wells), and develop the relations between two line-like objects or two point-like objects. For completeness, cardinal direction relations and distance relations are also introduced in the proposed context. Finally, we implement the framework to extract roads and moving vehicles from an aerial photo. The promising results suggest that our methods can be a valuable tool in defining rules for object based image analysis. 相似文献
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