决策支持系统中数据访问语言的研究

通过对目前面向问题求解的决策支持系统中数据访问机制的研究 ,设计了一种数据访问语言 (DAL)及其解释模型 ,从而通过在数据需求和数据存储之间添加数据语义层 ,提供了统一的数据访问接口 ,提高了决策问题求解的有效性和EUD模式的可行性。

基于本征正交分解的柔性多体系统动力学降阶研究

基于浮动框架与有限元方法建模的柔性多体系统,有限元节点坐标数量庞大,将会令动力学方程的求解时间显著提升。针对此问题,提出了基于本征正交分解(POD)和压缩感知结合的柔性多体系统的降阶方法。首先,对各部件弹性体动力学响应先验数据进行本征正交分解得到各弹性体的本征正交模态向量;其次,利用压缩感知与稀疏的本征正交模态坐标,将微分/代数动力学方程求解问题转化成稀疏本征正交模态坐标的范数优化求解问题,并且求解过程可以保持约束方程的成立。通过数值算例实验,与传统的隐式数值积分方法相比,该方法可减少72.47%的计算时间,且最大相对误差为6.089e-5,证明该方法可以在保证数值精度的情况下,减少计算时间,提高仿真效率。

Mining association rule efficiently based on data warehouse

The conventional complete association rule set was replaced by the least association rule set in data warehouse association rule mining process. The least association rule set should comply with two requirements: 1) it should be the minimal and the simplest association rule set; 2) its predictive power should in no way be weaker than that of the complete association rule set so that the precision of the association rule set analysis can be guaranteed. By adopting the least association rule set, the pruning of weak rules can be effectively carried out so as to greatly reduce the number of frequent itemset, and therefore improve the mining efficiency. Finally, based on the classical Apriori algorithm, the upward closure property of weak rules is utilized to develop a corresponding efficient algorithm.

我最喜爱的一件玩具

我已经读四年级了,还玩玩具吗?可以告诉你:玩！你可别笑,别的玩具我都不玩了,只对一件玩具感兴趣。什么?——七品芝麻官。 它有一顶黑色的官帽,那官帽分两层,上层又窄又小。