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   high-dimension 在 气象学 分类中 的翻译结果: 查询用时:0.048秒
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high-dimension
相关语句
  高维特
    A High-dimension Feature Spaces Clustering and Corresponding Weather Classification for Multi-spectral Satellite Images
    多光谱卫星云图的高维特征聚类与降水天气判别
短句来源
    According to weather sampling data from static GMS-5 images,the projections of IR1,IR2,VS WV in high-dimension feature spaces such as gray degree,grade degree and veins can be clustered. In this way,we can get to know the subject area of each weather sample in the feature spaces,so that we can get the weather classification of each nephogram.
    基于静止气象卫星(GMS-5)多光谱云图的天气采样数据,分别对各样本数据在红外、水汽及可见光通道的灰度、梯度和纹理高维特征空间的投影点进行聚类分析,以确定诸天气样本在特征空间中的类属区域,进而用其对云图进行天气区的判别分类。
短句来源
    Based on the sample data of GMS-5 stationary satellite, a high-dimension spectral feature space combining with gray and grads values of infrared, vapour and visible light channels images was constructed, and corresponding clustering analysis was performed.
    用GMS-5静止气象卫星多光谱云图的天气采样数据构造了红外、水汽和可见光通道的灰度、梯度高维特征空间,进行了采样数据的聚类分析。
    Finally, the clustering regions of the various weather kind in the high-dimension spectral feature space were divided up by computing a actual image's gray and grads values and judging their mapping location in the high-dimension feature space, the weather kind of the image pels is distinguished, and the auto classification of the satellite cloud image is also carried out.
    最后可得到高维特征空间中各类天气的类属空间区域,实况云图中的诸象素点通过计算和判断其灰度-梯度特征量在高维空间中的投影点落区位置,即可确定其天气类属,进而实现对天气区的自动分类。
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  high-dimension
The machine conceptually implements the following idea: input vectors are non-linearly mapped to a very high-dimension feature space.
      
The machine conceptually implements the following idea: input vectors are non-linearly mapped to a very high-dimension feature space.
      
Low-and high-dimension limits of a phase separation model
      
The Belinsky-Zakharov inverse scatteringmethod is extended to a double high-dimension form.
      
Algorithms of determining maximum (in modulus) complex-conjugate eigenvalues are considered as applied to finding eigenvalues of high-dimension matrices according to the Khilenko method.
      
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Based on the concept of attractors of nonlinear system, the phase space with higher dimension is reconstructed by using observed single meteorological time series and then the weather attractor is embedded in it. The dimension of weather attractor and the weather predictability can be estimated from the time evolution of initially close pieces of trajectories. Computation results used daily data sets of the general circulation index at 500 hPa in Asia and Beijing temperature in wintertime show the fractal dimensions...

Based on the concept of attractors of nonlinear system, the phase space with higher dimension is reconstructed by using observed single meteorological time series and then the weather attractor is embedded in it. The dimension of weather attractor and the weather predictability can be estimated from the time evolution of initially close pieces of trajectories. Computation results used daily data sets of the general circulation index at 500 hPa in Asia and Beijing temperature in wintertime show the fractal dimensions of 3.8 and 5.4 for these two attractors, respectively; and for which predictability time scale of 6-14 days, while weather predictability time scale of 4-9 days resulted from the e-folding expansion of trajectories in phase space.

本文从非线性系统的吸引子概念出发,用单个气象时间序列重构维数较高的相空间并嵌入天气吸引子,根据相轨道上初始时刻紧邻的点随时间的演化来估计吸引子的维数和天气的可预报性。用500hPa亚洲环流指数和北京冬季气温的逐日资料计算表明,天气吸引子的维数分别为3.8和5.4;可预报时间尺度约6—14天,考虑相空间e指数膨胀因素后为4—9天。

The difficuities in forecasting weather result from non-linearity、high—dimension and data’s lack of preciseness.Consequently’we take advantage of Artificial NeuralNetwork to solve meteorological problems. Back-Propagation network is used to forecast the intensity of Southwest Vortex’s rainfall over the southwestern part of Shandong province in China.After learning by itself,network automatically abstracts the relationship between predctors and predictand from historical data.Finally,we areable to make a comparably...

The difficuities in forecasting weather result from non-linearity、high—dimension and data’s lack of preciseness.Consequently’we take advantage of Artificial NeuralNetwork to solve meteorological problems. Back-Propagation network is used to forecast the intensity of Southwest Vortex’s rainfall over the southwestern part of Shandong province in China.After learning by itself,network automatically abstracts the relationship between predctors and predictand from historical data.Finally,we areable to make a comparably ocrrect prediction by means of BP network.

天气预报的困难主要源于非线性、高维性和数据的不精确性。所以,我们利用人工神经元网络来处理气象问题。本文引入BP网络来预报鲁西南地区的西南涡降水强度。经过网络的自学习,它能自动地从历史资料中抽取预报因子和预报对象的关系,进而作出较正规的预报。

From the viewpoint of system theory, the concept of complex large system for flood disaster is put forward, and some aspects of its characteristics such as high dimension, dynamics and complexity are discussed. Based on the comprehensive methodology with qualitative and quantilative integration, the comprehensive methodology of flood disaster analysis such as simulation, forecasting and evaluation as well as decision are investigated. Therefore,...

From the viewpoint of system theory, the concept of complex large system for flood disaster is put forward, and some aspects of its characteristics such as high dimension, dynamics and complexity are discussed. Based on the comprehensive methodology with qualitative and quantilative integration, the comprehensive methodology of flood disaster analysis such as simulation, forecasting and evaluation as well as decision are investigated. Therefore, it will provide the scientific basis for investigating the methodology for the management and control on flood disaster, and it is helpful for improving the relationships among resource and environmant as well as social development.

从系统论的观点出发,提出了洪水灾害复杂大系统的概念,讨论了该系统的组成特征及其高维性、动态性、复杂性等特征和基于定性与定量的综合集成方法,探讨了洪水灾害系统模拟、预测、评估与决策的综合分析方法。为进一步开展洪水灾害的管理与调控方法的研究奠定了基础,并将有利于促进资源、环境与社会的协调发展。

 
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