1) time series data mining
时序数据挖掘
1.
A new time series data mining system based on Gray Regression Fuzzy Neural Network hybrid model is proposed in this paper and the establishing process of this hybrid model was mainly discussed.
该混合模型融合多种智能计算方法优点于一体 ,为时序数据挖掘提供了一种新的实用方法 。
2.
Time series data mining is of great importance to development of society, sci.
本论文首先介绍了本课题的背景、研究内容和研究意义，论述了数据挖掘、时序数据挖掘的研究现状，包括它们的研究内容、常用方法以及当前的研究重点和发展方向。
3.
Focusing on the disadvantages of the current ball mill pulverizing system optimization approa- ches,a ball mill pulverizing system optimization algorithm based on fuzzy time series data mining is pro- posed.
针对以往制粉系统优化算法的不足,本文提出了一种基于模糊时序数据挖掘的火电厂制粉系统优化算法。
2) temporal data mining
时序数据挖掘
1.
To overcome the demerits of traditional trend sequences analysis in temporal data mining,two concepts that were number trend sequences and trend sequences unwrapping were put forward.
针对时序数据挖掘中传统趋势序列分析的缺点,提出了数字趋势序列、趋势序列展开等概念。
2.
To overcome the defects of data representation algorithms in temporal data mining,segmentation algorithm of key-point-based error checking is proposed.
针对时序数据挖掘中常见数据表示算法的缺陷,提出了基于关键点的误差检验分段算法。
4) time series data mining technology
时间序列数据挖掘技术
6) spatial-temporal data mining
时空数据挖掘
1.
Currently,the common data model of the spatial-temporal data mining has the strong application directive property and low general applied capability.
针对当前时空数据挖掘中常用数据模型具有较强应用指向性,通用性不强的问题,基于面向对象建模的思想,提出一种属性特征与时空关系一体化的时空数据模型,定义并详细给出了该模型的元素组成、信息范畴及元素间的相互关系,并以城市规划中地区建设变化为例验证此数据模型的有效性。
2.
As the spatial-temporal data increasing cosmically and data mining theories developing continuously, spatial-temporal data mining has become a research hotspot of experts and scholars in fields of computer and geography information system.
随着时空信息数据的大规模增长，数据挖掘理论的不断发展，时空数据挖掘已经成为计算机界及地理信息系统专家学者研究的热点。
补充资料：数据挖掘研究院
数据挖掘研究院（china data mining research,cdmr）是一个专注于数据挖掘及其相关技术的讨论组织，参与者都是数据挖掘及其相关学科的爱好者。作为论坛的组织者我们也是数据挖掘的忠实爱好者，希望能够利用一些有限的资源为中国数据挖掘营造一个良好的发展环境。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条