prior probability
英 [ˈpraɪə(r) ˌprɒbəˈbɪləti]
美 [ˈpraɪər ˌprɑːbəˈbɪləti]
网络 前概率; 验前概率; 先验概率; 事前概率; 事前机率
双语例句
- New adaptive algorithm for segmenting image background based on prior probability model
基于先验概率模型的自适应背景图像分割算法 - The second step is to evaluate for BN, decide prior probability and conditional probability.
再为贝叶斯网络赋值，确定先验概率和条件概率。 - Because the methods are all based on prior probability, their applicability is constrained.
这些方法均在不同程度上要求专家给出一些先验概率值，从而影响了它们的应用程度。 - The proportion based on the assistant data is used as the prior probability to replace the prior value in the conventional supervised classification; the farther iterative prior probability is applied into classifying progress on Landsat TM image.
由辅助数据中计算各类别面积比率作为先验概率，替换传统监督分类中的先验值，并进一步对先验概率进行迭代，最后利用改进的先验概率对LANDSATTM影像进行分类实验。 - First, the occurrence of all the system states is considered to have an equal possibility and for each component in the diagnosis system set a prior probability.
该模型首先假设系统的所有状态都是可能发生的，并对系统中的各个元件设定一个先验概率。 - Considering two stages probability method of maximum likelihood classification ( MLC), this article proposed a new method of exploiting spatial information to improve classification rules by adjusting the prior probability according to the local spatial information.
考虑到传统最大似然分类（MLC）方法包括先验概率和条件概率密度函数两个核心环节，提出基于空间信息的浮动先验概率MLC方法，融合空间信息和波谱信息，以提高分类精度。 - This method does not need prior probability and membership functions, and it can avoid the redundancy rules meanwhile. All of this made the system configuration optimization and can accelerate the system run speed.
从结果来看，采用该方法不需要先验概率，也不需要隶属函数，同时还可以去除冗余的局部决策，使系统的配置最优化、提高了系统的运行速度。 - The method evaluates the parameters of the joint distribution using the expectation maximization ( EM) algorithm. The minimum mean squared error ( MMSE) estimator for the speech feature parameters in spectrum-domain based the prior probability distribution is to enhance the correctness of speech recognition.
该方法采用期望最大化（EM）算法来估计联合分布参数，基于语音和噪声的先验概率密度，在倒谱域中对语音特征参数进行最小均方误差预测（MMSE），以提高语音识别精度。 - In the process of decision with risks, if we using sampling theory, the best decision in prior probability and modified posteriori probability can be obtained.
在进行风险型决策过程中，若能结合抽样理论，就可以以最低的代价找到先验概率下及修正后的后验概率下选择最优决策方案。 - The Bayesian Networks model is a new model for data expression and learning. It has no strict precondition of normal distribution of the input data and can increase the classification accuracy efficiently though adjusting the prior probability density dynamically.
贝叶斯网络是一种新的数据表达和推理模型，对数据没有严格的正态分布前提要求，通过动态地调整先验概率密度，能有效提高分类精度。 - We utilized joint distribution of Gaussian prior probability to compensate noise and channel simultaneously, and the result was that the channel mismatch between training environment and testing environment decreased.
本文利用联合高斯先验概率分布对噪声和信道同时进行补偿，以减少训练环境和测试环境的信道不匹配。 - Expected utility model based on fuzzy prior probability
基于模糊先验概率的期望效用模型 - In the supervised classification, the election and passivation of the AOI and confirmation of the prior probability are described, and the principle of the maximum likelihood classification based on Bayes rule in the paper is introduced.
在监督分类中，对训练区（AOI区域）的选择、钝化及先验概率的确定作了描述，并介绍了本文中采用的建立在贝叶斯（Bayes）准则基础上的最大似然分类法的原理。 - Secondly, it is unneeded to obtain the prior probability in course of rough sets theory application.
而且，应用粗糙集理论不需要事先确定事件的先验概率。 - The method of probability and statistics is difficult to obtain the prior probability of the occurrence.
大部分融合算法对于不完备、不确定数据的处理有很大的缺陷，例如，概率统计方法而且需要知道事件的先验概率，这在实际中是很难解决的问题； - The joint distribution of prior probability is estimated using the Expectation Maximization algorithm in detail. And we utilized joint distribution of Gaussian prior probability to compensate feature parameters. The parameter estimation formula of joint Gaussian Mixture Model was also derived.
在此基础上，引入倒谱的动态差分特征，采用期望最大化算法，估计先验概率的联合分布，利用联合高斯先验概率进行特征补偿，并推导了联合高斯混合模型的参数估计公式。 - Supported by the analysis and advance process to the geographical data using GIS software, the paper discusses the question that whether the accuracy of Bayes supervised classification will be improved considering the influence of the prior probability.
本文尝试利用GIS软件对地理数据进行分析和预处理，对考虑先验概率是否提高Bayes监督分类精度这一问题作了探讨。 - First, the least biased prior probability distribution of observed index under the given constraint condition is derived using the principle of maximum entropy.
本文先应用了最大熵原理来确定在给定约束条件（即已知信息）下，实测指标最小偏差的先验概率分布。 - Bayse classify is a statistical method based on Bayes theorem, which uses prior probability and sample information to calculate the posterior probability.
贝叶斯分类是一种基于贝叶斯定理的统计学分类方法，它是结合先验信息与样本信息计算出后验概率。 - A Method of Learning Prior Probability
先验概率值的一种学习方法 - The prior probability can be estimated by using the equivalence of the Markov random fields and the Gibbs Distribution ( GD).
先验概率可以根据马尔可夫随机场（MRF）和吉布斯分布（GD）的等效性，用GD的概率估计。 - Simulation results preferably indicate that, under the estimated a prior probability, an approach to image segmentation is superiority.
仿真结果表明在先验概率估计下的图象自动分割具有明显的优势和较大的应用潜力。 - The difficulty of subjectivity lies in the problem of constraint of prior probability in Bayesian inference mechanism.
对贝叶斯主义的主观性诘难，主要在于贝叶斯推理机制的先验概率的约束问题。 - And because the results based on Bayesian posterior probability classification, taking advantage of prior knowledge, so it can amend prior probability, and make sure the decision-making is more scientific and credible.
而且基于贝叶斯后验概率结果的分类，充分利用了先验知识，并修正了先验概率，使决策更具有科学性和可信性。 - In the initial iteration of the algorithm, using MAP algorithm to estimate the prior probability distribution of the received signal, it is more accurate than using the SIC algorithm. The SIC algorithm was used in the iterative process, to facilitate the calculation and implementation.
该算法在初始迭代采用MAP算法估计接收信号的先验概率分布以获得较精确的先验概率分布，迭代时采用SIC算法以方便计算和实现，仿真说明该算法有效地提升了系统的均衡效果。 - Comparison with the traditional setting, this method does not require a large database support, complex operation, but could set a more credible prior probability for the Bayesian networks. So, it has certain advantages.
与传统的设置方法比较，这种方法既不需要庞大的数据库支持，也不需要复杂的操作过程，但却能为贝叶斯网络设置一个比较可信的先验概率，因此具有一定的优势。 - The prior probability is amended by Bayesian probability model in the fusion process.
在融合过程中以贝叶斯概率模型修正先验概率。 - The fault diagnosis arithmetic based on Bayes test method and the significance-test of time statistics of the transition was put forward. Under the guidance of modular fault diagnosis idea, stratify and locate the fault source combined with prior probability and posterior probability of the system.
提出了基于Bayes试验方法的故障诊断算法，对变迁的时间统计量进行显著性检验，结合系统的先验和后验概率，在模块化故障诊断思想的指导下，分层定位至故障源。 - In this paper, we propose a new qualitative abstraction of Bayesian networks& PQPNs ( prior qualitative probabilistic networks) that focuses on the prior probability distribution.
本文提出一种新的贝叶斯网络定性抽象方法：先验定性概率网，其关注点为节点的先验概率与后验概率之间的关系。