• The paper gives the algorithm for mining time-series pattern or rules and illustrates the...

    给出了时间序列模式规则挖掘算法举例说明该算法是有效和可行的。

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  • The main task of data mining includes correlation analysis, cluster analysis, classification, prediction, time-series pattern, deviation analysis and so on.

    数据挖掘任务主要关联分析聚类分析、分类预测时序模式偏差分析

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  • In the paper, being directed to the complex model of time-series pattern, drawing idea and giving pseudo code of the algorithm of finding time-series patterns has been presented.

    针对时序数据中的复杂模式问题,提出了一种时序模式算法并描绘算法基本思想给出算法简单伪代码

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  • This paper imported an algorithm which was based on the pattern representation of time series extract outlier value.

    提出一种基于时间序列模式表示提取时间序列异常的异常检测算法

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  • The similarity pattern query about time series is one of the research hotspots in knowledge discovering in the time series database.

    时间序列相似性模式搜索营销时间序列数据仓库知识发现领域一个研究热点

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  • Epsilon machine, a new computational mechanics, can discover hidden pattern from the response time series.

    一种新的计算力学理论,它时间序列中发掘系统的隐含模式

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  • SVM applications, such as pattern recognition, function approaching, time series prediction, fault prediction and recognition, information security, power system and power electronics, are described.

    归纳了支持向量机在诸如模式识别函数逼近时间序列预测故障预测识别、信息安全电力系统以及电力电子领域中的应用

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  • Recently the study on data mining of time series mainly concentrates on both the similarity search in a time series database and the pattern mining from a time series.

    时间序列存在于社会各个领域,对于时间序列数据挖掘研究目前主要集中相似性搜索模式挖掘上。

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  • By making use of the proximity query method in computational geometry, the whole matching query, pattern query, inverse query and outlier detection in time series are studied.

    提出了计算几何应用时间序列挖掘方法,实现时间序列序列匹配查询模式查询、反向查询异常检测,查询效率和准确性都有了比较大的提高。

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  • Use a method of time series piecewise linear representation based on feature points as a way for pattern representation.

    使用一种基于特征时间序列线性分段方法作为时间序列的模式表示。

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  • The idea is to transform the net audit data into time series database and mine the sequence pattern to extract the user behavior pattern , and then to use behavior pattern in anomaly detection.

    思想通过网络审计数据转化为时序数据库,对其进行序列模式挖掘提炼用户行为模式,由此进行异常检测。

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  • It involves statistics, profiling and pattern recognition, behavioral analysis, time series analysis, predictive modeling, visualization, cause-and-effect studies and more.

    涉及到统计分析模式识别行为分析时间序列分析,预测建模可视化因果研究等等

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  • According to the change pattern of some parameters in metal cutting processes, this paper proposes for the first time a new time series analysis model-Autoregressive Constant model ARC (2).

    本文根据切削过程一些参数变化规律,从理论上首次提出一种新的时间序列分析模型,即系数固定价ARC(2)模型。

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  • The pattern representation of time series itself has the function of compress data and keeps the basic shape of time series, and it has a certain extent effect of deleting noises.

    时间序列模式表示本身就具有压缩数据保持时间序列基本形态功能并且具有一定噪能力

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  • Some of these maps illustrate the temporal pattern of the subject over a defined period of time while others show finer spatial details through a series of maps drawn in larger scale.

    每组地图显示主题特定时期内空间分布情况的变化,或透过一系列高比例的地图显示更多资料细节。

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  • Mining Time Series Frequent Sub-pattern based on Pattern Representation can enormously increase the efficiency and veracity of mining, and get twice the result with half the effort.

    时间序列模式表示基础挖掘其频繁子模式,可以大大提高挖掘效率准确性,达到事半功倍效果。在算法中,还使用了一定的剪枝策略,使得算法的时间复杂度进一步降低。

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  • Mining Time Series Frequent Sub-pattern based on Pattern Representation can enormously increase the efficiency and veracity of mining, and get twice the result with half the effort.

    时间序列模式表示基础挖掘其频繁子模式,可以大大提高挖掘效率准确性,达到事半功倍效果。在算法中,还使用了一定的剪枝策略,使得算法的时间复杂度进一步降低。

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