时间序列数据

基于SAX方法的股票时间序列数据相似性度量方法研究

Research on the Stock Time Series Data Similarity Based on SAX

一种支持时间序列数据的CBR检索算法

A CBR algorithm supporting time series data

改进SVM及其在时间序列数据预测中的应用

Modified SVM and Its Application to Time Series Forecasting

两种NDVI时间序列数据拟合方法比较

Comparison of two fitting methods of NDVI time series datasets

利用时间序列数据挖掘（TimeSeriesDataMining，简称TSDM），可以获得数据中蕴含的与时间相关的有用信息，实现知识的提取。

By mining patterns from time series data , we can get useful information related to time hidden in the database , thus implement extraction of knowledge .

本文首先运用FamaFrench四因素模型对股票组合的时间序列数据进行了回归分析。

First , I perform time-series tests on portfolio returns using Fama-French three factor model .

NDVI时间序列数据集重建方法述评

Research on the Reconstructing of Time-series NDVI Data

基于NOAA时间序列数据分析的中国西部荒漠化监测

Application of NOAA-AVHRR to Desertification Monitoring for Western China

实践证明，Rough集理论作为一种处理模糊和不确定性问题的有效工具，对于时间序列数据的挖掘同样也是有效的。

Practice proves that rough set theory , as an effective tool to deal with vagueness and uncertainty , is also effective to the time series data mining .

阐述了基于Rough集的时间序列数据的挖掘策略，重点讨论了时间序列数据中的时序与非时序信息的获取问题。

This paper proposes time series data mining strategy based on a rough set . It mainly discusses the acquisition of time-dependent and time-independent information from time series data .

笔者进一步采用时间序列数据模型，运用协整分析与格兰杰检验的方法，研究了FDI与本土技术创新之间的关系。

Moreover , by the analysis of co-integration and Granger Causality Test , time series model was used to study the relationship between FDI and indigenous innovation .

应用ART算法对2006年至2009年某市行业招工的时间序列数据进行分析，预测某些行业的劳动力需求趋势。

Through the application of ART algorithm into the analysis of the time sequence data of recruitment in XX City from 2006 to 2009 , the trends of labor demand in certain industries can be predicted .

第三章是用反卷积分析事件相关fMRI时间序列数据的理论部分。

Chapter Three is the theoretical part of using deconvolution analyzing time series datas of event related fMRI .

对东中西部时间序列数据进行格兰杰因果关系检验的结果表明，在东部地区和中部地区，FDI是经济增长的原因；

FDI is the cause of economic growth in the Eastern and Middle Regions , Economic growth is also the cause of FDI inflow in the two regions .

基于NDVI时间序列数据的土地覆盖变化检测指标设计

Study on Land Cover Change Detection Method Based on NDVI Time Series Datasets : Change Detection Indexes Design

GMM方法不仅在通常的截面数据或时间序列数据中有着重要的应用，它在PANELDATA模型中的相关理论与方法也具有重要的理论意义和研究价值。

Despite it has an important application in regular cross section data or time series data , GMM method has the important theoretic meaning and researching value in panel data model .

利用NDVI时间序列数据分析植被长势对气候因子的响应

SVI and VCI Based on NDVI Time-Series Dataset Used to Monitor Vegetation Growth Status and Its Response to Climate Variables

通过对前馈神经网络时间序列数据预测网络模型的建立方法及预测方法讨论，基于BP网络对股票数据进行实际预测。

Establishing of prediction network model in multiplayer feedforward neural network ′ s time series prediction and the prediction design measures are discussed , based on BP network the stock data are forecasted .

在对跨国直接投资理论分析的基础上，选取改革开放三十年来我国利用跨国直接投资流量与我国GDP的经济数据组成时间序列数据。

Granger causality and co-integration test are employed to analyze the time series data formed by the thirty-year GDPs data on flow and the annual FDI data after Chinas reform and opening up .

然后用PCA方法对NDVI时间序列数据进行信息增强与压缩处理，以排除各种干扰因素，提高分类精度。

Secondly , in order to improve the classification accuracy , the authors performed a PCA transform on the NDVI time series data to remove noises .

对投资流量、资本存量、GDP等时间序列数据建立模型测算、回归分析，得出重庆市资本存量较多、整体投资使用效率较高的结论；

The research establishes the regression model on the data of the investment flow , the investment stock and GDP , and finds the investment stock is sufficient and the investment efficiency is high .

通过构建理论模型，并以中国1983-2003年时间序列数据为样本，得出结论认为：人力资本水平的丰裕程度决定了FDI技术溢出的大小；

Through the establishment of theoretical model and the use of serial data from 1983 to 2003 , this paper finds that the quantity and quality of human resource capital determines the technology spillover .

基于1982-2003年对外直接投资与出口贸易的时间序列数据，采用向量自回归（VAR）模型方法，实证分析对外直接投资对出口贸易的影响。

This paper examines the relationship between outward foreign direct investment ( OFDI ) and exports from China during the period of 1982-2003 by employing a vector autoregressive ( VAR ) system .

为刻划心脏节律存在的确定性动力学特征，运用不稳定周期轨道分析方法对健康青年人的RR间期时间序列数据进行分析。

To characterize the deterministic dynamics in heart rhythm , the unstable periodic orbit analysis were the RR interval time series of healthy young men .

本文提出了一种用于稻麦病虫害预测的新方法&基于案例推理的时间序列数据的相似年分析（CBR），并主要对其预测因子、参数进行了优化筛选。

A New method , based on case-based reasoning ( CBR ) in time series data similarity analysis , was studied used in the forecast of crop diseases and pests .

所以本文结合经验模式分解和径向基神经网络建立时间序列数据流在线预测模型一OnlineDSPM。

Therefore , in this paper combined with empirical mode decomposition and radial basis neural networks establish one online time series data stream prediction model called Online_DSPM is proposed .

灰色预测模型GM（1,1）与马尔柯夫链结合成为灰色马尔柯夫预测模型，可以有效提高随机波动性较大的时间序列数据的预测精度。

We can effectively improve the prediction accuracy of time-series data regardless of its large random volatility , when we combine the Grey Predicting Model GM ( 1,1 ) and MARKOV CHAIN into MARKOV Predicting Model .

因此，如果利用灰色预测模型GM（1,1）对时间序列数据进行处理，寻找时间序列数据发展的趋势，马尔柯夫链的不足之处就可以弥补。

When processing the time-series data in the use of Grey Predicting Model GM ( 1,1 ) to figure out the development trend of time-series data , the inadequacy of MARKOV CHAIN can be made up .

利用S-G滤波进行MODIS-EVI时间序列数据重构

Reconstruction of MODIS-EVI Time-Series Data with S-G Filter

采用BP神经网络逼近非线性插值方法构建等时距时间序列数据，在此基础上建立沉降变形时间序列的GM模型，并建立相应的时间响应函数，预测沉降量。

Constructing the equal-time settlement time series data by BP neural network nonlinear interpolation method , on the basis of it , building the time series GM model for settlement , and building the time function to predict the settlement .