Online analytical processing expands the framework of data from two-dimensions to multiple-dimensions and provides the method to analyze the multi-dimensional data.
联机分析处理把数据的组织由二维平面结构扩充到多维空间结构，并提供了多维数据分析方法。
Proposed dynamic clustering algorithm has strong robustness in clustering of time series multi-dimensional data.
本文算法对于时序数据的聚类具有较强的鲁棒性。
Based on the study of designing pattern of multi-dimensional data model, three designation methods are pointed out.
研究了多维数据模型的设计模式，给出了三种主要的设计方法。
Maintenance management in the tobacco industry introduction to operation cost, the cost of access to multi-dimensional data.
在烟草企业检修管理中引入作业成本法，可以获得多维度的成本数据。
A dynamic clustering algorithm was proposed based on consistent matrix of dependent function for time series multi-dimensional data.
根据时序立体数据的特点，提出了基于关联函数一致性矩阵的动态聚类算法。
CART decision tree has outstanding advantages on the issue of classification in dealing with multi-dimensional data with complex structure.
决策树能实现快速分类，CART决策树在处理复杂结构的多维数据分类问题上具有突出优势。
A new visualization method for resource searching based on parallel coordinate is presented to map multi-dimensional data to two-dimensional space.
提出了一种基于平行坐标可视化技术的查找新方法，将资源多维状态数据映射到二维空间。
It also discusses the concept and features of online analyzing and processing (OLAP), multi-dimensional data structure and multi-dimensional data analysis.
讨论了联机分析处理OLAP的概念、特性、多维数据结构、多维数据分析等技术。
This system can provide the queries of multi-dimensional data cube and also obtain the mining analysis though the mining algorithm for supporting decision-making.
系统可提供进销存多维数据立方体的查询，还可以通过挖掘算法进行挖掘分析以辅助决策。
Typically, online aggregation algorithms on multi-dimensional data need additional auxiliary data for estimation, which make the performance of the storage and maintenance of the data cube worse.
以往在数据立方体上实现的联机聚集往往需要附加空间来存储联机聚集估算所需要的信息，极大地影响了数据立方体的存储和维护性能。
The DM and OLAP are the critical techniques of data analysis, the multi dimensional data mining model combining both techniques can enhance the performance and effects of data analysis.
DM技术与OLAP技术是电力营销决策支持系统中的关键数据分析技术，二者有机结合构成的多维数据挖掘模型能提高数据分析的效果和性能。
The DM and OLAP are the critical techniques of data analysis, the multi dimensional data mining model combining both techniques can enhance the performance and effects of data analysis.
DM技术与OLAP技术是电力营销决策支持系统中的关键数据分析技术，二者有机结合构成的多维数据挖掘模型能提高数据分析的效果和性能。
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