测试函数

  • 网络tests;Test function
测试函数测试函数
  1. 每个测试函数的调用被夹在setUp和tearDown调用之间。

    Each test function call is sandwiched between a call to setUp and tearDown .

  2. filter函数为列表的每个元素调用一个测试函数,测试函数返回布尔值,当测试函数返回True时,还包含列表的元素。

    The filter function calls a test function , which returns a boolean , on each element of a list and includes that element only if the test function returns True .

  3. 将双字耦合度函数和T-测试函数线性叠加构造新的统计量CT来识别语料库中的候选未登录词。

    The linear superposition of Two-word coupling function and T-test function can construct a new statistic CT to identify the candidate unknown words in the corpus .

  4. 这个数组应包含测试函数、测试装置(fixture)或同时包含两者。

    The array should contain test functions , test fixtures , or a mix of both .

  5. 利用旅行商问题(TSP)、随机优化算法测试函数对免疫算法及其他算法进行了测试分析。

    The convergent character of IA is tested using TSP problem and some test functions .

  6. 使用Matlab通过对4个测试函数的仿真验证,这种新型的遗传算法的寻优性能较之SGA(基本遗传算法)有了很大的提高。

    After authentication of four test functions by using Matlab , this new GA is better than SGA .

  7. 此外,九个标准测试函数用来测试PSO算法和其他几种流行的进化计算方法的性能,结果验证了PSO有着其他进化算法无法比拟的快速收敛等特性。

    Furthermore , nine benchmark functions are used to test the performance of PSO and other popular EC algorithms .

  8. 两个测试函数和FIR数字滤波器设计的实验结果说明这种改进的有效性。

    Experimental results of two testing functions and a FIR digital filter design show the validity of the improvement on fitness evaluation .

  9. 通过对典型测试函数寻优以及电动汽车防抱死控制系统的PID控制器参数优化整定的实验,验证了该算法的有效性。

    With some typical test functions and the PID controller parameter tuning problem of the ABS control system , the effectiveness of the proposed algorithm is verified .

  10. 在凸的及分布不均匀的这两个测试函数上,我们还使用了两个度量标准Cover和Spacing对算法进行定量的评价。

    Two evaluative methods : Cover and Spacing are used as the quantificational criterion for our algorithms on the test functions : convexity , non-convexity and non-uniformity .

  11. 对测试函数的仿真实验表明,与对比方法相比较,DSPSO算法具有更好的收敛精度和更快的进化速度。

    The simulation test shows : compared with the contrast method , DS-PSO algorithm has better convergence accuracy and higher evolution velocity .

  12. 最后,采用经典测试函数验证异步模式的有效性,测试结果表明:与同步模式(经典PSO算法)比较分析,异步模式的收敛速度显著提高,同时刻的寻优效果更好。

    The experiment results demonstrate that the asynchronous pattern has bigger speed of convergence and better optimizing result comparing with the synchronous pattern .

  13. 数值实验结果表明,本文算法能够高效处理这类测试函数,并且在非常少的演化代数就可以使得到的非劣解全部进化到Pareto最优解。

    The numerical experiment results indicate that , the proposed algorithm can deal with this kind of test functions highly effective .

  14. 测试函数的比较计算证明该算法能够在较短时间内搜索到更多均匀分布的Pareto解。

    Test functions testify that the novel algorithm can search more Pareto optima stretching along the Pareto front in a shorter time .

  15. 经用C++编程对经典的Shubert与Banana测试函数进行实验测试。

    Using C + + program , we have tested two classical functions-Shubert and Banana .

  16. 应用FGA对3个著名的优化方法测试函数进行优化计算。

    Three famous test functions of optimization method are calculated with FGA .

  17. 首先定义一个HTML文件来实例化此DOH、小部件,然后定义要执行的测试函数。

    Well , you define an HTML file that instantiates the DOH , instantiates widgets , then defines the test functions to execute .

  18. 通过对测试函数的寻优和汽油调合调度优化问题的求解,实验结果验证了该算法的有效性。(4)提出了一种具有种群禁忌剔除策略的DNA遗传算法。

    The algorithm is applied to find optimization of test functions and the gasoline-blending scheduling problem , and the results verified the proposed algorithm effectiveness . ( 4 ) A DNA genetic algorithm with population taboo eliminate strategy is proposed .

  19. 利用一组具有代表性的Benchmark测试函数对该算法进行测试,以此来验证该算法的有效性。最后,本文探讨了粒子群算法在基因表达数据聚类分析上的应用。

    This improved algorithm is tested by a group of Benchmark functions to verify its validity . Finally , the application of particle swarm optimization algorithm in gene expression data clustering is discussed .

  20. 文中又通过对几类标准测试函数的优化实验和同其他优化方法的寻优效果对比,从另一方面证明了本文IGA的有效性和优越性。

    Next , by optimization experiments on several kinds of standard test functions and the comparisons to another optimization algorithm the effectiveness and the superiority of IGA is proved in another way .

  21. unittest框架会在测试函数之间循环往复,先调用setUp、再测试函数、然后清除(tearDown)测试函数。

    The unittest framework will cycle through the test functions , calling setUp , the test function , then tearDown for each test function .

  22. 然后,可以像以前一样运行这个应用程序,并获得flatprofile或callgraph,应该会看到很多C运行函数,包括printf(这些函数在我们的测试函数中并不是太重要)。

    If you then re-run the application as before and obtain a flat profile or a call graph , you should see lots of C runtime functions including printf ( none of which are significant in our test program ) .

  23. 许多开发者遇到过这样的事情,写了一些标准的单元测试函数之后,就认为把对verify方法从测试函数移到tearDown函数更好。

    It occurs to many developers after authoring a few standard unit test functions that it would be better to move the call to verify from the test functions to the tearDown function .

  24. 通过五个典型测试函数的仿真实验,验证了其可行性,同时也表明具有随机惯性权重的PSO算法较具有线性递减惯性权重的PSO算法在收敛速度和全局收敛性方面有明显提高。

    The results of five benchmark functions prove the model to be feasible , at the same time show that the performance of the PSO with stochastic inertia weight is improved obviously than that of the PSO with linearly decreasing inertia weight .

  25. testParse09Rss是真正的测试函数。

    TestParse09Rss is the actual test function .

  26. 完成所有的定义之后,便可以测试函数equalString和索引扩展。

    With all the definitions in place , you can test the function equalString and the index extension .

  27. HGA的有效性通过3个典型测试函数得到验证,并应用于拍合式继电器电磁系统的体积优化。

    The validity of HGA in this work was verified by three typical functions . Further more , an application was introduced for the volume optimization of electromagnet system of clapper-type relay .

  28. 通过一组高维测试函数对DCAS算法的性能进行了高达1000维的仿真实验。

    Extensive computational studies were also carried out to evaluate the performance of DCAS on a new suite of benchmark functions with up to1000 dimensions .

  29. 实验中选取标准的测试函数ZDT问题和DTLZ问题,采用特定的评价方法对两种算法的运行结果进行比较。

    The experiment chooses standard test functions ZDT and DTLZ , and use specific evaluation methods to compare two algorithms .

  30. TNK测试函数验证了提出算法具有良好的数据挖掘能力,并且可使非劣解具有更好的分布特性。

    It has been proved by TNK test function that the algorithm proposed has better data mining ability , and provides the non-inferior solution a better distribution characteristic .