2) time series data mining technology
时间序列数据挖掘技术
4) 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。
5) 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。
6) fuzzy time series data mining
模糊时间序列挖掘
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