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图划分的英文

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  • graphic partitioning

例句与用法

  • A problem on the computational complexity of graph partitions
    关于图划分中的一个计算复杂性问题
  • Modified voronoi diagram layout partition based substrate coupling parameter extraction technique using bem
    图划分的边界元衬底耦合参数提取技术
  • Experiments show that the new optimized partition algorithm can improve the parallel simulation performance compared with the ones partitioned by traditional graph partition algorithms
    实验表明,该优化划分方法相对于传统的图划分算法能够有效地提高模拟性能。
  • The structure design has been underway to the train diagram database on the basis of relationship database rules . and the concrete implementation scheme of train diagram distributed database has been analyzed and designed
    运用关系数据库原理对列车运行图数据库进行了结构设计,并对列车运行图划分布式数据库的具体实施进行了分析和设计。
  • One of the main problems in pdes is how to partition the network simulation workload to decrease the time needed to complete the simulation and improve performance of simulation . here a new optimized partition algorithm was put forward , which first analyses the performance factors of parallel simulation and then constructs a performance estimation model for partition ; based on this model , it mends the graph partition algorithm to consider all factors , including simulation applications and simulation environments . optimized factors are workload balance 、 communication cost and time window of lookhead
    鉴于基于传统图划分算法的任务划分工具存在诸多不足,本文提出了并行网络模拟任务的优化划分方法,其思想是:首先从pdes机制出发,分析影响并行网络模拟性能的各种因素并建立一个能够综合考虑各种因素的并行网络模拟性能估计模型;其次,改进多级图划分算法,使得算法具有综合考虑模拟应用与模拟运行环境,同时在优化过程中使用性能估计模型指导划分,实现对影响并行网络模拟性能的三个因素(包括负载均衡、通信开销、安全时间窗口长度)的优化能力;最后,结合并行网络模拟性能估计模型与改进的多极图划分算法,实现了并行网络模拟任务的优化划分。
  • The former one gains the aim of improving the recommended speed by grouping the transaction clusters , which make system has ability to solve the limitations of the collaborative filtering technology which ca n ' t process huge data . the latter one adopts hypergraph partitioning skill and effectively groups the association rules according to the users " historical visiting data
    基于关联规则聚类的推荐算法采用超图划分的技术,对根据用户的历史访问数据得到的关联规则进行有效的分组,可以找出不同兴趣用户群的相同访问模式,提高了推荐的质量。
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