Methods A sample survey based on stratified probability samples of 2 204 students aged 12~21 years old among 11 schools in four districts of Shanghai was carried out.
方法采取分层整群随机抽样的方法，对市内四个区11所学校的2 2 0 4名12～21岁的在校学生进行不记名问卷调查。
In the process, we calculate the posterior probability of semantics by unlabeled samples information.
在计算的过程中，使用了未标记样本的信息计算语义出现的后验概率。
The background samples are chosen by thresholding inter-frame differences, and the Gaussian kernel density estimation is used to estimate the probability density function of background intensity.
通过相隔固定的帧差值阅值化得到背景样本值，并采用高斯核密度估计方法计算背景灰度的概率密度函数。
The probability based matching(PBM) search on mass spectral data not only provides pure samples results (with forward PBM search), but also separates compounds in a mixture (with reversed PBM search).
质谱匹配概率方法不仅能提供纯样品的分析结果，而且也能区分混合物中的成分。
In this algorithm, sample region density is introduced. Weight vectors are updated under the condition of selecting samples with different probability according to their density.
该算法引入样本区域密度的概念，根据密度大小按不同的概率选取样本，以修正权矢量。
In the paper, we use the statistical theory to calculate the probability of video semantics by Bayesian formula, choose the semantic of maximal probability to label the unlabeled samples.
文中采用统计学理论，利用贝叶斯概率公式计算视频语义出现的概率，选取概率最大的类别标注未标记的样本。
The article also introduces several experiments using samples with different probability distribution and 2d images to compare the performance between the classic and improved algorithm.
文中介绍了若干实验，对多种分布的样本以及2维图像进行了经典算法和改进型算法的比较。
With the accumulated and improved training samples, it automatically modifies the parameters of network structure and probability distribution.
该模型还可以通过不断积累完善训练样本，自动修正网络结构参数和概率分布参数。
SD as the initial model to the maximum a posteriori probability method in 150 training samples to identify the best, can reach 90.4 .
以SD为初始模型的最大后验概率方法在150个训练样本时识别效果最好，可以达到90．4％ 。
On the basis of test data, this paper gives the probability distributions of the limit tensile strain of large full graded samples and small wet screened ones.
根据实测资料，给出了全级配混凝土大试件和与其对应湿筛后混凝土小试件拉伸极限应变的概型分布；
The data adopted in calculation directly source from the samples, and thus the reliance on the existing data and the classical probability distribution functions is reduced.
在计算中，采用的数据直接来源于样本，减少了对已有数据和经典概率分布的依赖。
A probability multiplication formula was used as the theoretical foundation. The PNN structure was optimized based on statistical results from the PCA for the training samples.
以概率乘法公式为理论依据，根据训练样本的PC A结果对PNN进行结构优化，并引入学习算法减小pnn的参数不确定性。
A probability multiplication formula was used as the theoretical foundation. The PNN structure was optimized based on statistical results from the PCA for the training samples.
以概率乘法公式为理论依据，根据训练样本的PC A结果对PNN进行结构优化，并引入学习算法减小pnn的参数不确定性。
应用推荐