The key idea of mining association rules for the basket data is studied and several methods to improve algorithm efficiency and rules selection are given.
对零售业销售数据关联规则挖掘算法的关键思想进行了研究，给出了各种提高算法效率的方法以及对规则选择的方法。
These work show that, we can effectively improve algorithm efficiency and increase value by using CUDA parallel technique in cutting and packing problem solving.
基于以上研究工作，本文采用的CUDA并行技术应用在切割与布局问题求解中，可以切实提高算法的求解效率，增加工程效益。
The improved task distribution and load balancing strategy avoid imbalance load on computing nodes and job jam in pipeline, and improve the efficiency of the algorithm.
改进的任务分配与负载平衡策略，避免了节点机负载的不平衡和流水线作业的积压，提高了算法的效率。
应用推荐