Chinese translation for "隐含并行性"
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- implicit parallelism
Related Translations:
条件隐含: conditional implication
- Example Sentences:
| 1. | And because of its independence , global optimization and implicit parallelism , ga is developed and applied by more and more people
由于其具有不依赖于问题模型的特性、全局最优性、隐含并行性等特点，正越来越激起人们研究与应用的兴趣。 | | 2. | Ga is a computational models of the human evolution , with implicit parallelism and capacity of using effectively global information
遗传算法( ga )是一种通过模拟自然进化过程搜索最优解的方法，其显著特点是隐含并行性和对全局信息的有效利用能力。 | | 3. | Thirdly , genetic algorithm is a kind of search and optimization method simulating the life evolution mechanism , which has the advantages of global optimization and implicit concurrency
遗传算法是一种模拟生命进化机制的搜索和优化方法，与常规优化算法相比，具有隐含并行性和全局搜索特性，因此选择遗传算法进行寻优计算。 | | 4. | The paper discusses the basic theory of genetic algorithms including schemate theorem , building block hypothesis , implicit parallelism , the analysis of astringency and so on , as the theoretical base of application
在对遗传算法的阐述中，讨论了遗传算法的基本原理，包括模式定理、积木块假设、隐含并行性和遗传算法的收敛性分析等，作为后面遗传算法应用的理论依据。 | | 5. | Compared with traditional optimization methods , genetic algorithm has two notable characters . one is the latent parallelism and the other is searching in the whole area . genetic algorithm has some advantages which traditional methods do n ' t have
与常规的优化算法相比，遗传算法具有隐含并行性和全局收敛性两大显著特征，并且具有常规优化方法所没有的优点，如不需要梯度计算等。 | | 6. | In this text , we first do some research on the genetic algorithm about clustering , discuss about the way of coding and the construction of fitness function , analyze the influence that different genetic manipulation do to the effect of cluster algorithm . then analyze and research on the way that select the initial value in the k - means algorithm , we propose a mix clustering algorithm to improve the k - means algorithm by using genetic algorithm . first we use k - learning genetic algorithm to identify the number of the clusters , then use the clustering result of the genetic clustering algorithm as the initial cluster center of k - means clustering . these two steps are finished based on small database which equably sampling from the whole database , now we have known the number of the clusters and initial cluster center , finally we use k - means algorithm to finish the clustering on the whole database . because genetic algorithm search for the best solution by simulating the process of evolution , the most distinct trait of the algorithm is connotative parallelism and the ability to take advantage of the global information , so the algorithm take on strong steadiness , avoid getting into the local
本文首先对聚类分析的遗传算法进行了研究,讨论了聚类问题的编码方式和适应度函数的构造方案与计算方法,分析了不同遗传操作对聚类算法的性能和聚类效果的影响意义。然后对k - means算法中初值的选取方法进行了分析和研究,提出了一种基于遗传算法的k - means聚类改进(混合聚类算法) ,在基于均匀采样的小样本集上用k值学习遗传算法确定聚类数k ,用遗传聚类算法的聚类结果作为k - means聚类的初始聚类中心,最后在已知初始聚类数和初始聚类中心的情况下用k - means算法对完整数据集进行聚类。由于遗传算法是一种通过模拟自然进化过程搜索最优解的方法,其显著特点是隐含并行性和对全局信息的有效利用的能力,所以新的改进算法具有较强的稳健性,可避免陷入局部最优,大大提高聚类效果。 |
- Similar Words：
- "隐海百合" Chinese translation, "隐海扇属" Chinese translation, "隐含" Chinese translation, "隐含暗流的徘徊行情" Chinese translation, "隐含表" Chinese translation, "隐含波动率" Chinese translation, "隐含波动性" Chinese translation, "隐含参考" Chinese translation, "隐含操作" Chinese translation, "隐含层" Chinese translation
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