Many studies have focused on horizontal ground motion, resulting in many coherency functions for horizontal ground motion while neglecting related problems arising from vertical ground motion. However, seismic events ...Many studies have focused on horizontal ground motion, resulting in many coherency functions for horizontal ground motion while neglecting related problems arising from vertical ground motion. However, seismic events have demonstrated that the vertical components of ground motion sometimes govern the ultimate failure of structures. In this paper, a vertical coherency function model of spatial ground motion is proposed based on the Hao model and SMART 1 array records, and the validity of the model is demonstrated. The vertical coherency function model of spatial ground motion is also compared with the horizontal coherency function model, indicating that neither model exhibits isotropic characteristics. The value of the vertical coherency function has little correlation with that of the horizontal coherency function. However, the coherence of the vertical ground motion between a pair of stations decreases with their projection distance and the frequency of the ground motion. When the projection distance in the wave direction is greater than 800 meters, the coherency between the two points can be neglected.展开更多
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 b...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.展开更多
数字经济与实体经济融合(以下简称数实融合)已成为中国经济发展的新动力。为探究当前中国数实融合发展的现状和区域差异,首先在剖析数实融合发展内涵及机理的基础上,从融合条件、融合应用、融合效益三个维度构建评价指标体系,其次利用...数字经济与实体经济融合(以下简称数实融合)已成为中国经济发展的新动力。为探究当前中国数实融合发展的现状和区域差异,首先在剖析数实融合发展内涵及机理的基础上,从融合条件、融合应用、融合效益三个维度构建评价指标体系,其次利用纵横向拉开档次法对中国30个省区市2013—2020年数实融合发展水平进行测度,最后结合基尼系数与探索性空间数据分析法(exploratory spatial data analysis,ESDA)研究区域间融合发展的时空差异。实证研究结果表明:近几年中国数实融合发展水平持续上升,整体具有向好的发展态势;区域间发展差异明显,发展水平从东向西依次递减,融合发展水平最高的是广东,最低的是青海;在发展过程中,融合应用能力不足是制约发展的关键原因且地域间缺乏融合互动,在空间上表现出明显的正向集聚特征。本研究从战略指引、应用强化和区域合作等方面提出对策建议,可为各部门制定数实融合发展的相关计划提供参考。展开更多
基金Supported by National Natural Science Foundation of China Under Grant No.90715005,No.NCET-07-0186 and No.200802860007
文摘Many studies have focused on horizontal ground motion, resulting in many coherency functions for horizontal ground motion while neglecting related problems arising from vertical ground motion. However, seismic events have demonstrated that the vertical components of ground motion sometimes govern the ultimate failure of structures. In this paper, a vertical coherency function model of spatial ground motion is proposed based on the Hao model and SMART 1 array records, and the validity of the model is demonstrated. The vertical coherency function model of spatial ground motion is also compared with the horizontal coherency function model, indicating that neither model exhibits isotropic characteristics. The value of the vertical coherency function has little correlation with that of the horizontal coherency function. However, the coherence of the vertical ground motion between a pair of stations decreases with their projection distance and the frequency of the ground motion. When the projection distance in the wave direction is greater than 800 meters, the coherency between the two points can be neglected.
基金The work is supported by Natural Science Foundatiion of Chongqing (No .CSTC 2005BB2065)
文摘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.
文摘数字经济与实体经济融合(以下简称数实融合)已成为中国经济发展的新动力。为探究当前中国数实融合发展的现状和区域差异,首先在剖析数实融合发展内涵及机理的基础上,从融合条件、融合应用、融合效益三个维度构建评价指标体系,其次利用纵横向拉开档次法对中国30个省区市2013—2020年数实融合发展水平进行测度,最后结合基尼系数与探索性空间数据分析法(exploratory spatial data analysis,ESDA)研究区域间融合发展的时空差异。实证研究结果表明:近几年中国数实融合发展水平持续上升,整体具有向好的发展态势;区域间发展差异明显,发展水平从东向西依次递减,融合发展水平最高的是广东,最低的是青海;在发展过程中,融合应用能力不足是制约发展的关键原因且地域间缺乏融合互动,在空间上表现出明显的正向集聚特征。本研究从战略指引、应用强化和区域合作等方面提出对策建议,可为各部门制定数实融合发展的相关计划提供参考。
