在线字典为您在线查询元主的词典内容如下,包括元主的拼音,读音,拼读;元主的意思和详细释义,元主的近反义词,元主的英语翻译,用元主这个词语怎么造句等内容。
元主读音/繁体/五笔/英文翻译
拼音 | yuán zhǔ | 读音 | 跟我读 |
---|---|---|---|
繁体 | 元主 | 类型 | 词语大全 |
五笔 | 此词无五笔连打 | 平音 | yuanzhu |
词性 | 中性 | 语法 | |
拼读 | 元(yuan2)|知(zhi1)五(wu3),主(zhu3) | ||
英语翻译 | 多元主题timeline |
元主是什么意思?
· 基本释义
长公主。
· 详细释义
长公主。
清 吴伟业 《思陵长公主挽诗》:“元主甘从殉,君王入 未央 。”
· 网络释义
元主yuán zhǔ 长公主。清·吴伟业《思陵长公主挽诗》:“元主甘从殉,君王入未央 。”
元主的近反义词?
元主近义词:抱歉,查无元主的近义词
元主反义词:抱歉,查无元主的反义词
元主词语接龙
(~元主~)在开头的接龙:主人,主要,主机,主意,主力,主办,主席,主语,主旨,主观,主权,主食,主义,主角,主子,主管,主线,主流,主攻,主见
(~元主~)在结尾的接龙:公主,地主,君主,财主,债主,真主,领主,业主,自主,霸主,民主,苦主,盟主,神主,帮主,天主,房主,户主,货主,宾主
暂时无法为您进行元主的词语顺序接龙!
用元主怎么造句?
您好,暂未查询到元主造句的内容。
在该注释中,您将主依赖项指定一些相关的元数据(借助ivy的魔力,所有中间依赖项都可以悉数确定)。
In this annotation, you specify some relevant metadata regarding the main dependency. (Through the magic of Ivy, all transitive dependencies will be figured out too).
这样做的原因是因为WS - Security规范允许为身份验证附加多个令牌,这样就需要更多的元数据来识别哪一个是主安全令牌。
You need to do this because the WS-Security specification allows attaching multiple tokens for authentication, thus additional metadata is required to identify which is the primary security token.
一旦我们选择了段管理器,EVMS会在磁盘上存放一些元数据,同时创建主引导记录并将磁盘上的剩余空间标记为“freespace”,使之用于新段。
Once we choose a segment manager, EVMS will put some metadata on our disk, creating a master boot record and marking the rest of the space on our disk as "freespace," available for new segments.
该产品主险责任涵盖由甲型流感导致的身故和医疗费,保额最高达15万元人民币,保费则根据客户选择的保额档次从几十元到几百元。
The premium of the insurance, which is the first of its kind in China, varies from dozens to hundreds of yuan, and the maximum coverage is up to RMB150000.
Registry andRepository是用于服务交互端点描述的主元数据存储库。
Registry and repository is the master metadata repository for service interaction endpoint descriptions.
Registry是用于服务交互端点描述的主元数据存储库。
Registry is the master metadata repository for service interaction endpoint descriptions.
WebSphereServiceRegistry andRepository是用于服务交互端点描述的主元数据存储库。
WebSphere Service Registry and Repository is the master metadata repository for service interaction endpoint descriptions.
根据RationalSystemsDeveloper设计的DSL利用ecore模型提供领域专用的建模支持,直接从主AUTOSAR 元模型生成。
The DSL tool designed on Rational Systems Developer provides domain-specific modeling support using an ecore model, which is directly created from the master AUTOSAR meta-model.
MasterDataRepository包含主数据(实例和定义)、MDM系统的元数据以及修改主数据的历史记录。
The master data Repository consists of master data, both instance and definition master data, metadata for the MDM System, and history data that records changes to master data.
每一元素倾向于既满足它的主价又要满足它的副价。
Every element tends to satisfy both its primary and secondary valence.
一个Atom订阅源由一个主元素feed组成,其中包括一些初始的元数据(例如,订阅源标题、作者、URL、它引用的全部内容的URL)。
An Atom feed consists of a single main feed element, which includes some initial metadata (for example, the title of the feed, any authors, its URL, and the URL of the overall content it refers to).
如果目标是一个属性引用:引用中的主元表达式被求值。
If the target is an attribute reference: the primary expression in the reference is evaluated.
基于这个变量体系,我们运用主元因素分析法编制了一个可反映上市公司治理水平的综合指标——G指标。
Applying the principal component analysis method (PCA) to these variables, we compile a single composite index (G-Index) to rank Chinese listed firms' corporate governance levels.
在多变量统计过程控制中,传统的方法主要包括主元分析和偏最小二乘,这些方法存在着诸多缺陷。
Principal component analysis (PCA) and partial least squares (PLS) are the conventional techniques of multivariate statistical process control but exist some defects.
应用主元分析方法将高维数据转换到低维数据空间,这使得过程监测可以在低维的空间内进行。
High dimension was changed into low dimension by using principal component analysis method, process detecting could be carried out in the low dimension space.
讨论了基于多尺度主元分析的故障传感器数据重构问题。
Multi-Scale Principal Component Analysis for data reconstruction of the faulty sensor is discussed.
论文提出了一种基于改进的自适应主元提取算法的人脸识别方法。
An improved adaptive principal component extraction algorithm based face recognition method is proposed in this paper.
本文提出了一种选主元迭代法。对一类发散的线性系统讨论了其收敛性,并举例说明之。
In this paper, We developed a select main element iterative method. For a class linear system of divergence discussed convergence, and illustrate by examples.
根据超声多普勒血流信号和血管壁搏动信号的统计特性,提出了一种基于主元分析的非线性滤波方法。
A nonlinear filtering method based on principle component analysis (PCA) was proposed according to the statistical characteristics of the Doppler ultrasound blood flow signal and wall thump signal.
本文提出了一种基于主元分析法(PCA)的多模板字符识别算法。
This paper presented a new multi-template character recognition method based on principal component analysis(PCA).
应用基于主元分析的故障诊断方法对浮式油轮生产储油卸油系统进行故障检测与诊断研究。
Used fault diagnosis method based on Principal Components Analysis to research the fault monitoring and diagnosis of Floating Production Storage and Off-loading system.
该方法首先利用核主元分析对人脸图像进行特征提取,然后依据支持向量机与最近邻准则对所提取的核主元特征进行分类识别。
Firstly KPCA is used to extract the features of human face image, and then SVM combined with the nearest distance rule is used for classification, which depends on the kernel principal components.
列阵透镜由多个列阵元拼接而成,用以改善主透镜焦点附近能量分布的均匀性。
Lens array consists of many array units, which can improve energy distribution uniformity around the focus of main lens.
为了提高道路识别算法的鲁棒性和自适应性,提出了基于局部统计特征和主元分析的道路识别算法。
A new road recognition algorithm based on local statistical features and principal component analysis is introduced to improve its robustness and adaptiveness.
尝试性地将基于主元分析的多变量统计方法应用于连铸结晶器过程的监测。
The authors try to use multivariate statistics method based on principal component analysis (PCA) to monitor continuous casting mould process.
多主元高熵合金是一种新型的合金材料,是多种元素处于领导地位的合金。
High entropy alloy is a kind of advanced alloy, which multiple elements are in the leading positions.
为此提出了一种多向核主元分析(MKPCA)算法用于间歇过程的建模与在线监测。
A method based on multiway kernel principal component analysis (MKPCA) was proposed to capture the nonlinear characteristics of normal batch processes.
基于主元分析(pca)的统计检测方法已经被广泛应用于各种化工过程的故障检测和识别。
Numerous statistical process monitoring methods based on principal component analysis (PCA) have been developed and applied to various chemical processes for fault detection and identification.
基于主元分析(pca)的统计检测方法已经被广泛应用于各种化工过程的故障检测和识别。
Numerous statistical process monitoring methods based on principal component analysis (PCA) have been developed and applied to various chemical processes for fault detection and identification.
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