time series data

In this paper, we extract rules of the decision table by an incremental algorithm for the dynamic decision table of the time series data.

It provides tools for empirical work with time series data and is an introduction into the theoretical foundation of time series models.

Data mining in the time series similarity search was applied to hydrological time series data for mining similar hydrological processes.

Vegetation index time-series data has been widely used in land cover classification and ecological regionalization.

Objective: Fit the forcast model that suit to the time series data of the Hospitalization Expenses of Injury Children.

Longitudinal data is different for each individual observation time obtained by the cross-section and time series data together.

In the last part we give an extended neoclassical growth model, and use time-series data of China economic transition.

Time series data with observations recorded for each period in an associated calendar.

As the important area of data mining research, time-series data mining and forecasting have developed greatly.

Time series data is continuous and can be stored in a nested table or in a case table.

RRDtool is an open source, high performance data logging and graphing system for time series data.

Objective To fit the prediction model that suit to the time series data of the medical service demand.

Conclusions AR-GARCH model is suitable for analyzing heteroscedastic time-series data of infectious diseases.

Graphite is a Python web application that has been developed to provide scalable storage and visualization for numeric time-series data.

This section focuses on how time series data can be monitored using control charts.

By calculating the longest common subsequence , finally, similarity searching in time-series data sets is realized.

The process of knowledge discovery in time series includes preprocessing of time series data, attributes reduction and rules extraction.

We present a two-stage method for obtaining both phase and object estimates from phase-diversity time series data.

Absrtact: It is the most basic and frequent treatment that to carry on trend analysis to the time - series data.

Based on this design, algorithms are proposed for efficient analysis of time-series data streams.

RRD is a system to store and display time-series data (i. e. networkbandwidth, machine-room temperature, server load average).

At the same time, however, the nonlinear and chaotic characteristic of time-series data makes the mining be a difficult issue.

Using the analyzation of time series data, the relation of the pest population time series data and climate's factors was studied.

In this paper, the similarity mining method for time series data is investigated.

Returns predicted future or historical values for time series data.

Reactor noise experiments by using acquisition system for time series data of pulse train.

In this paper, the outlier mining method for time series data is investigated.

Time series data is a series of observational data according to temporal sequence.

A regression analysis is performed to test the hypothesis by 1952-1960 time series data.

Time series data is the data set that arranges every one according to the time, and it uses social, economic and technologic fields widely.

Time series data mining is of great importance to development of society, science and technology and economy to the people.

On the other hand, time series data showed much less change in the savings proportion over the years.

Time series data mining attracts more and more attention.

Firstly, series important point as segmentation point can compress high-proportionally time series data in this algorithm;

Analysis of Seasonal Dynamics of Vegetation Change in Shaanxi Province Based MODIS NDVI Time Series Data

Analyzing the characteristics of short-term anomalous information of GPS time-series data before earthquake

Modeling Capability of Evolving Recurrent Neural Network for Time Series Data and Correlative Data Series

Classification of chaotic time series data based on the average length of close orbits

analyzes trajectories of real estate investment and economic growth by citing related time series data;

Study on regression analysis and prediction of time-series data streams using sliding windows

Spectral analysis of time series data analysis methods in hospital application

Stochastic Subspace Model Identification and One-step Prediction for Time Series Data

Applying fuzzy time-series data mining for the fuzzy modeling of complex system

Differentiation Methods for the Memory of Time Series Data

Application of linear regression on aggregation of time-series data

Research of New Similarity Measure Method on Time Series Data

Time series data mining using discrete wavelet transform

A New Method of Separating Systematic Errors from Hydrographic Time Series Data

An Adaptive Forecasting Method for Time-Series Data Streams

Studies on the time series data nature population of the Hemiberlesia pitysophila Takagi

Time Equalized Interpolation and Rule Discovery in Time-Series Data

Method of Feature Extraction Suitable for Hyperdimensional Time Series Data

Robust Optimization Segment for Time Series Data

Weak limited periodic patterns mining on time series data

Research on the Attribute Reduction and Rule Acquisition of Time-Series Data Based on Rough Entropy

A novel similar matching algorithm for time series data

Modeling Approach of Transition Function Model, Based on Time Series Data of Air pollution and Health

Similarity search over time series data using DCT

Algorithm for Finding Similar Patterns over Time-Series Data Based on Wavelets and Feedback

Time Series Data Analysis and Pre-processing

Extracting Similar Patterns in Time Series Data

Fast discovering frequent patterns in financial time series data based on data mining

Statistical time series data base;

A CBR algorithm supporting time series data

Detecting Outlier Patterns in Time Series Data

Algorithm of Inverse Query on Time Series Data

Research on meteorological time series data mining based on quotient space

Time series data mining algorithm based on generalized computing

Research on similarity mining in time series data sets

Stock Market Time Series Data Mining Based on Regularized Neural Network and Rough Set

Fault Prediction for Rotating Machinery Based on Time Series Data Mining

Time Series Data for Climate Change

Research of Time Series Data Based on Exploratory Analysis

Novel Algorithm for Time Series Data Mining Based on Dynamic Time Warping

Diffusion Effect of Fertility Decline in China: An Analysis of the Province Level Time Series Data

Temporal Association Rules Mining Based on Time Series Data

A new algorithm of outlier mining in time series data

Time Series Data Mining Technique Based on Varying Series

Unit root test of time series data

Outlier Mining for Time Series Data Based on Outlier Index

A System of Time Series Data Mining Based on Hybrid Model