这就是拟建的新机场模型。
本文提出了一种用于图像分割的分层随机场模型。
This paper proposes a hierarchical random field model for segmentation of images.
提出了一种基于马尔科夫随机场模型的缺陷检测方法。
A method of vane defects detecting based on Markov random field is presented in this paper.
引入土层剖面随机场模型，把土性参数的点变异性和空间变异性联系起来。
Point variability and spatial variability of soil property parameters are associated by means of stochastic field model of soil profile.
分析、设计和实现了一个基于条件随机场模型的汉语分词和词性标注模块。
We analyzed, designed and achieved a module of Chinese word segmentation and Part-Of-Speech Tagging based on Condition Random Fields model.
根据条件随机场模型和马尔可夫随机场模型建立了一个最大后验概率框架。
Firstly, maximum a posteriori framework is created according to conditional random field model and Markov random field model.
根据分层吉布斯随机场模型，采用小波函数分级拟合均值曲面，提出了二值化方法。
By using the multi resolution analysis to interpolate the mean values based on hierachical model of Gibbs random field, a method for binary sketch of grey imagre was proposed.
针对旅游领域，提出了一种基于层叠条件随机场模型的旅游领域命名实体识别方法。
This paper presents a method for named entity recognition in the tourism domain based on the cascaded conditional random fields.
根据自然红外纹理在空间的统计分布特性，利用随机场模型可以有效地合成红外纹理。
The random field models can be available in synthesizing the natural texture according to the statistical distribution of intensity of texture in space.
在图像的多分辨率小波分析的基础上 ，采用高斯 -马尔可夫随机场模型来描述图像的局部特征 。
The hierarchical multiresolution wavelet analysis in conjunction with the contextual information of the image extracted from GMRF results in local features of the image.
本文从分数布朗随机场模型的描述出发，提出并构造了一种广义多尺度分形参数，用于描述图像的纹理信息。
In this paper, a kind of generalized multiscale fractal parameter is proposed and constructed for the description of image textures, which is based on fractional Brownian random field model.
文中通过利用马尔可夫随机场模型，引入图像象素的局部结构信息，有效实现了SAR目标切片图像的高精度分割。
Utilizing MRF (Markov Random Field) model to introduce the pixel's local context information, a quite accurate segmentation of SAR target chip image is realized.
我们利用条件随机场模型抽取领域实体对象，并将其应用于比较句识别和比较关系抽取中，取得了良好的实验效果。
We use CRF model to extract domain entities which are applied to identify comparative sentences and mine comparative relation with good results.
在许多采用马尔可夫随机场模型的基于样图的纹理合成算法中，邻域的大小决定着这些合成算法的纹理合成质量和合成速度。
For many sample-based texture synthesis algorithms using markov random field model, the size of neighborhood determines the quality and speed of texture synthesis.
其次，本文选用了一种将基于统计方法的条件随机场模型与基于规则方法的词性筛选模型相结合的方式对中文问句进行语义角色自动标注。
Secondly, this paper proposed a method combined rule-based pos selection model with Statistics-based Cascading Conditional random field to conduct semantic Role Labeling of Chinese Question.
基于图像在小波域的马尔可夫随机场模型(MRF)结构，结合SAR图像中相干斑噪声的统计特性，本文提出了一种新的小波域相干斑抑制方法。
Integrating the statistical characteristics of speckle noise in SAR images with wavelet-domain Markov random field (MRF) structure of images, a new wavelet-domain spec.
针对遥感图像分布的不均匀性，该文提出的算法没有采用固定的马尔可夫随机场模型参数，而是在递归分类算法中分级地调整模型参数以适应区域的变化。
As the MRF model with fixed parameters does not fit the real remotely sensed image very well, this paper adjusts the MRF model "s parameters during the classification procedure."
针对遥感图像分布的不均匀特性，该文提出的算法没有采用固定的马尔可夫随机场模型参数，而是在递归分类算法中分级地调整模型参数以适应区域的变化。
As the MRF model with fixed parameters does not fit the real remotely sensed image very well, this paper adjusts the MRF model's parameters during the classification procedure.
采用传统图像检测方法存在目标区域定位不准确、目标细节信息丢失、目标形状变形等问题，本文提出一种基于离散分数布朗随机场模型的水下图像目标检测方法。
To overcome the shortcomings of traditional methods, a method of underwater image segmentation based on the discrete fractional Brownian random field was proposed to dispose underwater images.
这个C型模型将有更低的噪声特性，它能使机场周围的居民和支付燃料账单的航空公司一样高兴。
The -c model is designed to have a lower noise profile to keep people around airports as happy as the airline bean counters paying the fuel bills.
缺少可靠治理模型的SOA实现无异于一个没有指挥塔的机场。
Implementing SOA without a solid governance model is the equivalent to having an airport without a control tower.
利用定量模型和GIS方法，从空间布局、服务范围以及航空客流分布等方面来研究中国的机场体系及其服务水平。
Based on the quantitative model and GIS method, this paper analyses the airports' spatial distribution, service coverage and air passengers flow in China.
针对民用机场多因素气象预测问题的复杂性，该文构建出一种基于粗糙集的模糊神经网络模型。
For a multifactor weather prediction problem, this paper constructs a new model of fuzzy neural network based on rough set.
条件随机场是一种无向图模型，它具有产生式模型和最大熵马尔可夫模型的优点。
Conditional Random Fields (CRF) is arbitrary undirected graphical model that bring together the best of generative models and Maximum Entropy Markov models (MEMM).
模型还充分考虑了机场容量、需求以及天气等因素的动态特性，在达到和出发过程之间实现流量分配的协同决策。
The model considers the dynamic characteristics of airport capacity, traffic demand, and weather to makes decision on the flow distribution between arrivals and departures.
结果表明，模型能够较准确地预测出机场的旅客吞吐量。
Experimental results show that the model can be exactly applied in the forecast of airport passenger throughput.
重点研究了AMDB数据绘图映射和建模方法、机场三维模型与地形的合成显示技术。
The AMDB mapping and modeling method, the synthesis display technology of airport 3D model and terrain were studied emphatically.
重点研究了AMDB数据绘图映射和建模方法、机场三维模型与地形的合成显示技术。
The AMDB mapping and modeling method, the synthesis display technology of airport 3D model and terrain were studied emphatically.
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