The performance improvement after the application of each tuning parameter is cumulative, building upon the parameters from the previous sections.
根据上一节所提供的参数，调节各调优参数后实现的应用程序性能改善是可以累加的。
By applying the rules discussed earlier, this health check exercise indicates that no further tuning effort is required for the NUM_IOCLEANERS parameter.
通过应用前面所讨论的规则，该健康检查实践表明NUM_IOCLEANERS参数不需要进行进一步的调优工作。
On OLTP systems, where user sessions are performing quick queries, tuning this parameter can be very important.
在OLTP系统上，用户会话执行快速查询，调节此参数可能非常重要。
In the chart, the blue bars always represent the baseline throughput values and the red bars represent the throughput values after adjusting the discussed tuning parameter.
在该表中，蓝柱用于表示基准吞吐量值，而红柱表示调整所讨论的调优参数后的吞吐量值。
This is the main parameter for JVM tuning.
这是用于JVM调优的主要参数。
For detailed information on JVM parameter tuning, refer to [5].
要获取关于JVM参数调优的详细信息，请参考[5]。
There is a brief explanation of each parameter with a recommended 'default' value followed with some data that illustrates the importance of tuning GlassFish for performance.
每个参数都有一个建议的缺省值、简要介绍以及说明其对于性能影响重要程度的数值。
The time slice tuning parameter allows the user to specify the number of clock ticks by which the time slice length is to be increased.
时间片调整参数允许用户指定时间片长度增加的时钟计时数。
The final parameter is used for passing additional tuning parameters through to PDO or the underlying driver--more on that shortly. Here's a short sample script that connects to DB2
最后一个参数用于传递附加的调优参数到PDO或底层驱动程序 —— 后面很快会有更详细的论述。
With AIX Version 5.3, changing the lru_file_repage parameter is a far more effective way of tuning, as you would prefer AIX file caching not be used at all.
在AIXVersion 5.3中，更改lru_file_repage参数是一种更加有效的优化方法，因为您希望不要使用AIX文件缓存。
PID parameter tuning and optimizing is an important issue in the field of automatic control.
PID参数整定与优化一直是自动控制领域研究的重要问题。
You can determine a good starting point for tuning your configuration by using the configuration Advisor, which recommends database parameter values based on your system resources.
您可以通过使用Configuration Advisor确定调优配置的良好起点，Configuration Advisor基于您的系统资源来推荐数据库参数值。
The self-tuning memory is enabled using the self_tuning_mem database configuration parameter.
自调优内存特性可以通过self_tuning_mem数据库配置参数来启用。
The amount of "anticipation" is decided by the value of tuning parameter.
预期的总量决定于其调谐参数的值。
This method efficiently makes use of expert experience in PID parameter tuning, and the controller has the merits of both fuzzy control and PID control.
此整定方法有效地把专家经验应用于PID参数调节中，控制器集模糊控制器和PID控制器的优点于一身。
Simultaneously, some parameter tuning strategies are presented to guarantee low overshoot and good robustness for the predictive control system.
同时，本研究提出一些参数调谐策略，确保此预测控制系统具有低超越及良好的韧性。
The key issues in the study of PID parameter tuning are presented.
最后还指出目前PID参数整定研究的热门方向。
The design of PID parameter controller based on fuzzy self tuning is introduced.
提出了一种模糊自整定PID参数控制器的设计方法。
Then, the parameter tuning method via artificial fish school algorithm (AFSA) is proposed.
随后提出了采用人工鱼群算法进行参数整定的方法。
The FNIMC controller consists of a model inverse controller and a robustness filter with a single tuning parameter.
FNIMC由一个逆模控制器和具有一个可调参数的鲁棒滤波器组成。
Feedback control is a parameter self tuning fuzzy controller and the burn through point is calculated by quadratic curve method.
反馈部分为参数自调整模糊控制器，终点的计算采用二次曲线拟合法。
The conventional PID control system was not very suit for this type of system, because the conventional PID control can't accomplish online auto-tuning PID parameter adjust.
常规的PID控制对于这样的系统的控制效果不是很理想。 这是因为常规PID不能根据现场的情况进行在线自我调节参数。
A method to realize the parameter self tuning of the speed controller in a position servo system is proposed.
提出了一种位置伺服系统速度调节器参数自调整的方法。
The structure of the distributing system is used to increase the reliability and the intelligent PID parameter tuning method is adopted to enhance the control precision.
为提高可靠性采用分布式系统结构。为提高控制精度采用智能PID参数整定算法。
Based on the PID control theory and recent PID parameter tuning method, a tuning method using direct search optimization (LJ method) is designed.
本论文在PID控制理论及现有PID控制参数整定方法的基础上，设计使用随机数直接搜索法进行PID控制参数的寻优整定。
In this paper, a new automatic tuning method of PID controller based on dynamic neural network is proposed and an online parameter tuning algorithm is given out.
提出一种基于动态神经网络的PID控制器，给出pid参数在线自整定学习控制算法，并进行了算法仿真研究。
Parameter tuning of Support Vector Regression (SVR) has been a critical task to develop a SVR model with good generalization performance.
在回归支持向量机的建模中，参数调节问题一直是影响模型性能的重要因素之一。
Finally, two methods of PID control parameter self-tuning are studied.
最后，用两种方法就PID参数的整定问题做了进一步的研究。
Parameter tuning simulation experiment has been performed on this model.
最后对参数整定的结果进行了分析。
By using stair-like tactics, the calculation complexity of parameter tuning is reduced effectively, and it is easier to regulate the quality of the PID controller by changing stair factor.
利用阶梯式控制策略，有效地减小了参数整定中的计算复杂性，并能更方便地通过阶梯因子对所得pid控制器的控制性能进行调节。
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