Research in Temporal Association Rules Mining

数据挖掘又称数据库中的知识发现，是数据库研究最活跃的领域之一，这门技术自兴起以来因其广阔的应用前景和深远的现实意义受到学术界的广泛关注，而其中的关联规则挖掘问题，因其丰硕的研究成果和自身理论的逐渐成熟，正在形成一个比较完善的研究体系并带动整个数据挖掘技术快速发展。自从Agrawal等学者于1993年首先提出了关联规则挖掘问题以来，诸多的研究人员对关联规则挖掘问题进行了大量的研究，提出了很多高效的算法，然而大多数方法都未考虑时间因素的影响。但在现实世界中，时间是数据本身固有的因素，在数据中常常会发现时序语义问题。时序数据的出现使得有必要在数据挖掘中考虑时间因素，在现实中，附加上某种时序约束的规则...Data mining, also known as knowledge discovery in database(KDD),is one of the most active fields in database. After existing, because of its wide application background and realistic significance, this technology has been drawing upon the attention of academic circle. Association rules mining is one of the important research aspects of data mining. Because it has rich research fruits and its theor...学位：工学硕士院系专业：信息科学与技术学院计算机科学系_计算机应用技术学号：X20034303

Research and Realization of Integrated Environment for Data Warehouse

引入开放式设计思想,使得数据仓库集成环境具有很强的适应性,该集成环境架构在.NET平台上,采用组件开发技术,使系统具有良好的可靠性、可扩展性和安全性。The design of EDWIE(Integrated Environment for Enterprise Data Warehouse) adopts the open thought and the software is based on the.NET software architecture,so the flexibility,reliability,expansibility and security of this system are favorable.国家自然科学基金资助项目(50474033);; 福建省自然科学基金资助项目(A0310008);; 福建省高新技术研究开放计划重点项目(2003H043

Algorithm for mining calendar-based temporal association rules

以日历格作为框架来研究时序关联规则,提出了一个有效的挖掘算法。在用户指定的日历模式下,首先通过一次扫描产生所有的频繁2项集及相应的1*日历模式,在此基础上产生k*日历模式,并利用聚集性质产生候选K项集及相应的日历模式,最后扫描事务数据库产生所有的频繁项集及其日历模式。实验证明,该算法具有较好的性能。An efficient algorithm for temporal association rules based on calendar patterns was presented.A user-given calendar schema was adopted to specify the interesting rime intervals as calendar patterns.Then database was scanned once to find all frequent 2-itemsets and their 1-star calendar patterns.Aggregation property and Apriori property were utilized to find all candidate patterns.Finally,calendar-based temporal association rules were obtained through scanning.The experimental results indicate that this proposed algorithm is feasible and efficient.福建省自然科学基金资助项目(A0310008);; 福建省高新技术研究开放计划重点资助项目(2003H043

客车乘员座椅动态试验的仿真研究

依据GB13057-2014法规要求,应用Hypermesh软件建立客车座椅动态试验的有限元模型,接着调用HybridⅢ50%男性假人,调整其姿态,同时把已建好的有限元模型及调整好01.1的多面体假人进行耦合设置并提交计算。结果表明,仿真分析结果与试验结果在运动过程、变形情况、乘员伤害值等方面具有较好的一致性,仿真模型能够预测和代表试验段在试验测试中的力学行为,并为后期的座椅动态安全性优化提供可靠的依据

Discover Fuzzy Calendar-based Temporal Association Rules

基于日历约束的时序关联规则挖掘由于其实用性,越来越受到研究者的关注。由于现实中用户很难对时间模式进行精确描述,因此基于模糊日历的时序关联规则挖掘更有现实意义。借助模糊概念和模糊运算,对时间区间的描述很容易实现。对于用户指定的日历模式,不同的时间区间可根据它们的隶属度具有不同的权重。在模糊日历代数的基础上,结合增量挖掘和累进计数的思想,本文提出了一种基于模糊日历约束的关联规则挖掘方法,理论分析和实验结果均表明,该算法是高效可行的。Research of mining calendar-based temporal association rules is attracting more and more attention because of it's practicability. But in real life,it is impossible for user to describe the time accurately, so fuzzy temporal association rules are more useful. Based on fuzzy calendar algebra and fuzzy operators, it is easy to describe desired temporal requirements. Time intervals may have different weights according to their membership functions. Integrated with the ideas of progression and increment ,this paper presents a algorithm called BFCTAR to mine fuzzy temporal association rules. Theory analysis and experiment results indicate that this algorithm is efficient and feasible.福建省自然科学基金项目(A0310008);; 福建省高新技术研究开放计划重点项目(2003H043)

Mining fuzzy temporal association rules

借助模糊概念和模糊运算,对时间区间的描述很容易实现。对于指定的日历模式,不同的时间区间可根据它们的隶属度具有不同的权重。在模糊日历代数基础上,结合增量挖掘和累进计数的思想,提出了一种基于模糊日历的模糊时序关联规则挖掘方法。理论分析和实验结果均表明,该算法是高效可行的。With the help of fuzzy calendar algebra and fuzzy operators, it is easy to describe desired temporal requirements. Time intervals may have different weights according to their membership functions. Integrated with the idea of progression and increment, an algorithm combined with incremental mining and progressive counting called BFCTAR was proposed to mine fuzzy temporal association rules based on fuzzy calendar algebra. Theoretic analysis and experimental results indicate that this algorithm is efficient and feasible.福建省自然科学基金资助项目(A0310008);; 福建省高新技术研究开放计划重点项目(2003H043