一个参数标记或一个主变量。
您还研究了参数标记/主变量的使用会为DB2优化器对分布统计信息的考虑带来怎样的限制。
You have also examined how the use of parameter markers/host variables may limit the consideration of distribution statistics by the DB2 optimizer.
对全部输人特征参数进行了主变量分析,给出了采用不同数量特征参数的优化组合方案。
The optimum combinations adopting different numbers of characteristic parameters have been obtained by analyzing the main variables of all the input parameters.
使用主变量或实际文本时,DB 2不会对非索引考虑这个因素;只有您能够考虑这个因素并相应编码。
With host variables or literals, DB2 does not consider this factor for non-index predicates; only you can take this fact into account and code accordingly.
类似地,您还可以在用户从主屏幕导航到TSO应用程序时设置一个全局变量。
Likewise, you will also set a global variable when the user navigates from the main screen to a TSO application.
当用户从主屏幕导航到CICS应用程序时,将某个全局变量设置为CICS。
Set a global variable to CICS when the user navigates from the main screen to the CICS application.
对于主屏幕而言,应定义它的屏幕转换方法,并设置全局变量,以表明这个屏幕既非CICS,也非tso屏幕。
For the main screen, define how to transform that screen and set the global variable to indicate that the screen is neither a CICS nor TSO screen.
所有这些变量将在主循环中用到。
All these variables will be useful in the course of the main loop.
最后,输出使用从主规则的单词和ID创建的变量。
Finally, the output USES variables created from the words and the IDs of the master rules.
因此,您应仅执行该JNDI查询一次,然后存储所检索到的主对象(例如,存储在实例中或静态变量中)。
Therefore, you should perform the JNDI lookup once only, and then store the retrieved home object (for example in an instance or static variable).
然后,主脚本只需导入这个config .py并直接使用那些变量即可。
The main script can then just import the config.py and use those variables directly.
如果没有设置amgr_disablemaillookupNotes . ini变量,并将“newmail”代理设置为在非主邮件服务器上运行,那么代理将不会运行。
If the AMgr_DisableMailLookup Notes.ini variable is not set, and if the "new mail" agent is set to run on a non-home mail server, the agent will not run.
$entry变量的值被添加到主故事菜单文件和主题特定的故事菜单文件中。
The value of the $entry variable prepends onto the main story menu file and the subject-specific story menu file.
在主函数中的变量也叫全局变量,因为所有函数都可以访问这些变量。
Variables in __main__ are sometimes called global because they can be accessed from any function.
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.
并对影响城市空气质量的5个主要因素进行主成分分析,找出最能代表原来数据信息的2至3个因子代替原来的5个变量。
Then 5 main factors affecting urban air quality to principal component analysis identify the most representative of the original data instead of the 2 to 3 factors 5 variables.
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.
将微分进化算法扩展到可求解混合变量、有约束的船舶主尺度优化问题。
In this paper, the DE algorithm was expanded to solve the mixed variables, restricted principal dimensions optimization.
提出了把现代控制理论的状态变量观测与控制系统理论应用于主汽温度控制系统的方案和参数整定方法。
This paper put forward the scheme applying modern control theory-state variable quantity observation and control to boiler's main steam temperature control system as well as parameter tuning method.
介绍了主分量分析法的原理和步骤,由此构成的新矢量,降低了输入矢量的维数,提高了变量间的不相关性。
Comparing new input vector constructed by this method with that constructed directly, the dimension of input vector is decreased and capacity of orthogonal among the variables is enhanced.
然后利用层次类聚分析考察各指标之间的相关,同时分为五大类,利用主成分分析将其简化为不相关的变量。
Then-level analysis of the study the correlation between indicators, divided into five categories, using principal components analysis will be simplified for not related variables.
本文讨论多元质量数据的矢量分析方法,几何变换,坐标旋转和初始变量的主分量计算不同变量的主分量值。
This paper deals with the multivariate vector analysis of quality data by geometric transformation, rotating coordinates and computation of the principal component of initial variables.
事实上,它被认为是一种奖励当主成分变量实际上可以被破译。
In fact, it is considered to be a bonus when the principal component variables can actually be interpreted.
为了提高模型的预测准确率,使用了双变量统计和主成份对数据进行预处理和分析。
To improve the forecasting accuracy, bivariate statistics and PCA were used to prepare and analyze the data in advance.
当你在所有函数之外建立一个变量的时候,这个变量就属于主函数所有。
When you create a variable outside of any function, it belongs to__main_\.
概率主元分析(PPCA)能够根据过程变量的预测误差及其主元的白化值实现对过程的监控。
Probabilistic principal component analysis (PPCA) can realize the process monitoring (according) to the whiten values of process variables' prediction error and their scores.
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.
通过综合运用主成分分析和层次分析方法,建立系统综合评价的AHP变量加权主成分分析模型。
Using the methods of Principal Component Analysis (PCA) and the Analytical Hierarchy Process(AHP), the paper proposes the synthetic evaluating model of PCA with weighted variables by AHP.
该方法将主惯导数据测量延迟时间扩展为卡尔曼滤波器的一个状态变量,并同时考虑了测量延迟时间对速度和姿态测量量的影响。
The method augments the measurement delay as a state of conventional Kalman filter as a state, and impacts on both velocity and attitude measurements owing to the time delay are also considered.
该方法将主惯导数据测量延迟时间扩展为卡尔曼滤波器的一个状态变量,并同时考虑了测量延迟时间对速度和姿态测量量的影响。
The method augments the measurement delay as a state of conventional Kalman filter as a state, and impacts on both velocity and attitude measurements owing to the time delay are also considered.
应用推荐