Research on spatial association rules mining in two-direction

In data mining from transaction DB, the relationships between the attributes have been focused, but the relationships between the tuples have not been taken into account. In spatial database, there are relationships between the attributes and the tuples, and most of the associations occur between the tuples, such as adjacent, intersection, overlap and other topological relationships. So the tasks of spatial data association rules mining include mining the relationships between attributes of spatial objects, which are called as vertical direction DM, and the relationships between the tuples, which are called as horizontal direction DM. This paper analyzes the storage models of spatial data, uses for reference the technologies of data mining in transaction DB, defines the spatial data association rule, including vertical direction association rule, horizontal direction association rule and two-direction association rule, discusses the measurement of spatial association rule interestingness, and puts forward the work flows of spatial association rule data mining. During two-direction spatial association rules mining, an algorithm is proposed to get non-spatial itemsets. By virtue of spatial analysis, the spatial relations were transferred into non-spatial associations and the non-spatial itemsets were gotten. Based on the non-spatial itemsets, the Apriori algorithm or other algorithms could be used to get the frequent itemsets and then the spatial association rules come into being. Using spatial DB, the spatial association rules were gotten to validate the algorithm, and the test results show that this algorithm is efficient and can mine the interesting spatial rules.     

基于最小二乘支持向量机和证据理论的交通数据融合

针对基于浮动车辆数据(floating car data,FCD)的城市道路交通信息采集系统存在的问题,提出一种基于最小二乘支持向量机(LS-SVM)和证据理论的数据融合方法,通过融合地感线圈采集的交通流量信息,提高FCD系统交通速度信息采集的准确性.利用LS-SVM回归得到速度-流量关系曲线的临界速度参数,再根据历史数据库用统计方法计算出流量-速度关联规则的可信度矩阵,在得到这些经验知识的基础上,定义了两种证据源的基本概率分配函数.最后,通过D-S证据理论对两种证据源进行数据融合,获得融合后的速度信息.实地跑车实验结果论证了融合算法的有效性和可靠性.     

基于扩展的嵌套关系代数的关联规则挖掘查询

提出了一种使数据挖掘与数据库系统无缝集成的方案.该方案基于关联规则挖掘和关系数据库系统的通用查询算法,采用一种扩充的嵌套关系代数作为关联规则和其它数据查询的一种内部表达方式.通过一个典型实例展示了这种代数表达式.代数表达式也被表达为一种查询树,查询树中代数运算的公共操作序列模块化后,具有更多的灵活性,能方便地处理约束关联规则查询和其它各种关联规则描述.     

大熊猫精子发生及年龄,季节变化

本文首次系统地对不同季节，不同年龄大熊猫睾丸组织进行了精子发生的细胞学观察，以及曲细精发育的测定。大熊猫精子发生分批进行，在曲细精管切面，从基膜向管腔分别为精原细胞，初级精母细胞，次级精母细胞，精细胞及变态精子。     

Development and characterization of interspecific hybrids between <Emphasis Type="Italic">Oryza sativa</Emphasis> and <Subscript>O. latifolia</Subscript> by <Subscript>in situ</Subscript> hybridization

Oryza sativa and O. latifolia belong to the AA and CCDD genomes of Oryza, respectively. In this study, interspecific hybrids of these species were obtained using the embryo rescue technique. Hybrid panicle traits, such as long awns, small grain, exoteric large purple stigma, grain shattering and dispersed panicles, resemble that of the paternal parent, O. latifolia, whereas there is obvious heterosis in such respects as plant height, tillering ability and vegetative vigor. Chromosome pairing and the genomic components of the hybrid were subsequently investigated using genomic in situ hybridization （GISH） and fluorescent in situ hybridization （FISH） analysis. Based on the mitotic metaphase chromosome numbers of the root tips investigated, the hybrid is a triploid with 36 chromosomes. The genomic constitution of the hybrid is ACD. In the meiotic metaphase Ⅰ of the hybrid pollen mother cell, poor chromosome pairing was identified and most of the chromosomes were univalent, which resulted in complete male sterility in the hybrid.     

基于两阶段计数的用户关联挖掘

基于规则的推荐技术在数据集上挖掘项目关联和用户关联为当前用户做推荐．用户关联挖掘是使用用户关联进行推荐的关键．首先证明在整个数据集上挖掘到的关于当前用户的用户关联集是只在包含当前用户评价的数据集上挖掘到的关于当前用户的用户关联集的子集,提出基于两阶段计数的用户关联挖掘框架,然后应用概念格技术实现了基于两阶段计数的用户关联挖掘算法,并通过实验表明该算法具有更好的性能．     

对抗体系的一种建模方法研究

首先,通过实例阐明了信息交互在效能涌现中所起的重要作用;其此,提出了“基于信息关联网的体系建模方法”,为研究信息交互过程中对抗体系的效能涌现机理提供了方法论意义上的支持;最后,基于上述体系建模方法,给出了一个具体的建模实例。     

条件概率P（I/（A∩B∩C））上界的一个估计

设抽样空间为U,A,B,C是随机事件,I和I’是一对互补随机事件.故有下面的结果：如果π1＇（A,B,C）＞π1（A,B,C）＞0,那么P（I/（A ∩ B ∩ C）） ＜ P（I）/P（l＇） · P（A/I）/P（A/I＇） · P（B/I）/P（B/I＇） · P（C/I）/P（C/I＇）当P（I/（A ∩ B ∩ C））的上界是很小的正数时,且A,B,C这些因子同时发生时,可预测I’将要发生.     

强计算条件下判断矩阵的优选分析

针对AHP中对判断矩阵的研究大多侧重于一个判断矩阵的不足,以强计算为基础,通过计算大量矩阵的一致性比例、期望判断阵、特征值、关联度等方法,对多个判断矩阵进行比较分析,从中选择满足一致性要求的判断矩阵,并进行优化,使其包含较多的原始信息。最后通过实例,介绍了这种优选方法的基本步骤,验证了该算法的有效性。     

一种基于蚁群算法的数据关联方法

提出了基于蚁群算法的多目标跟踪数据关联方法--ACDA(Ant Colony DataAssociation).算法基于目标与量测之间的距离信息、角度信息和速度信息,依靠蚁群算法的优化机制,确定目标航迹和量测的正确关联,并且采用扩展卡尔曼滤波对目标状态进行估计.实验结果表明,该方法对应用在机动性较弱的高速小目柝数据关联时能够获得较高的正确关联率,且运行时间较短.