最后给出了模型性能验证数据，并加以分析。
At last, testing data of the model and the analysis is given.
此外，还对影响两种力学模型性能的参数进行了分析。
In addition, the parameters which affect the two models are also analyzed.
同时，从一致性和计算复杂度方面对模型性能进行了评价。
Simultaneously, this model performance was evaluated from the perspective of consistence and computational complexity.
因此paramics是一个验证交通分配模型性能优良的平台。
Thus, PARAMICS can serve as an excellent platform for validating traffic assignment models.
采用过抽样、欠抽样技术来弥补数据类别分布不平衡对模型性能的不利影响。
Sampling methods including over-sampling, under-sampling were taken to make up the shortage caused by the imbalanced data.
为了进一步提高模型性能，本文尝试了不同的特征模板集，并给出了对比的数据。
In order to improve the performance of the model, We have tried different feature template, and show the contrast data.
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。
Parameter tuning of Support Vector Regression (SVR) has been a critical task to develop a SVR model with good generalization performance.
这就说明了在SLM - CIR模型中，分词技术不是影响模型性能的关键因素。
This has proved that in SLM-CIR model, the technology of the word segmentation is not a key factor of influencing the performance of models.
提出了一种综合考虑了训练误差和检验误差的评价神经模糊模型性能的误差性能指标。
A performance index of error was presented. This index is a kind of evaluation of neural fuzzy model performance and synthetically considered training error and checking error of NFS.
此外本文通过分析不同主题数对本模型性能的影响，得出了适用于本模型的最佳主题数。
Furthermore, we also analyze the influence of the topic size in our model, and infer the fittest result to produce the best performance.
通过计算机实验，讨论样本、学习算法和网络结构等对神经网络预测模型性能的影响及其改进措施。
Through computer simulation, samples, BP algorithms and the influence of network structure neurula on model performance have been discussed as well as the improving measures.
为了获得最好的模型性能，挑选做出最合适假设的建模算法—而不只是选择你最熟悉那个算法，是很重要的。
In statistical modeling, there are various algorithms to build a classifier, and each algorithm makes a different set of assumptions about the data.
采用该方法进行新安江流域水文模型的参数优选，可以直接对模型性能进行全面评价，自动率定模型参数，显著提高了模型率定效率。
Using this model to calibrate Xinanjiang model can directly assess the model performance, calibrate the model parameter automatically, and significantly improve the efficiency of calibration.
在这些计时和内存使用量测试中，我使用的基本框架与以前的文档模型测试(请在参考资料中参阅作者有关文档模型性能的文章。)中所用的相同。
I used the same basic framework for these timing and memory usage tests as in my earlier tests with document models (see the author's document model performance article in Resources).
本文以宾州中文树库为实验语料，考查了不同规模的标注数据对模型性能的影响，实验结果表明，本文提出的无监督词性标注方法提高了中文词性标注的性能。
Experiments on Chinese TreeBank from different training set size are made. It shows that our approach improves the accuracy of POS tagging over the four training sets with different sizes.
持久性编程模型的复杂性和性能。
Complexity and performance of the persistence programming model.
通过对可使用性的极大改进提高了生产效率，改进了在大型模型上的性能，以及定制化安装您所需要的特定特性的能力。
Improved productivity through significant improvements in ease of use, improved performance on large models, and the ability to install just the features that you need.
例如，客户对象映射并不是性能测试模型的关键构件。
For example, client object maps are not a key component of the performance testing model.
常规使用时，RUNSTATS提供了在一段时期内有关表和索引的数据，从而随着时间的流逝，可以确定数据模型的性能趋势。
When used routinely, RUNSTATS provides data about tables and indexes over a period of time, thereby allowing performance trends to be identified for your data model as it evolves over time.
第2部分更深入地讨论这里介绍的一些概念，还要讨论领域模型中的性能调优。
Part 2 focuses in more depth on some of the concepts we discuss here and also covers performance tuning in the domain model.
团队承担了风险，因为不知道非功能性需求（如性能或线程模型）是否将得到满足。
The team takes a risk by not knowing whether the non-functional requirements (like the performance or threading models) will be satisfied.
为了简要地了解实际应用中的AXIOMAPI，我们将对一些示例进行研究，这些示例来自于对AXIOM与其他的文档模型进行性能测试对比的代码。
For a quick look at the AXIOM API in action, we'll look at some samples from the code used for performance - testing AXIOM against other document models.
第一项值得关注的事情，是我们十分重视可用性，处理了围绕性能，模型管理以及绘图的 200 多个用户需求。
The first noteworthy thing is we've worked hard on usability issues, addressing 200+ customer requests around performance, model management and diagramming.
航空学工程师将他们的模型放置在风道内来测量性能因素。
Aeronautical engineers take their models into wind tunnels to measure performance factors.
基准程序的焦点是为了显示每个模型的最佳性能；对于本文，我将尝试显示在每种模型中实现操作的最简便方法。
The focus in the benchmarks is to show each model at its best performance; for this article, I've tried to show the easiest way of accomplishing the operations in each model.
而且即使新功能可以避免新的“糟糕”程序，它也可能破坏现有的固定语言、用户期望或性能模型特征。
And even if the new feature doesn't enable new "bad" programs, it might undermine existing language invariants, user expectations, or performance-model characteristics.
然而，与性能类似，这个拓扑模型中与单元相联系的需求就代表了这个单元的需求。
Similar to capabilities, though, requirements are associated with a unit in the topology model to represent the needs of the unit.
一般情况下，性能模型遵循使用模型。
一般情况下，性能模型遵循使用模型。
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