time-series data

information collected over a number of time periods with respect to a given variable such as income. Compare CROSS-SECTIONAL DATA.

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- Simplified operations that allow users to focus on working with time-series data and eliminate the headaches of managing a database.

TIMESCALE INTRODUCES TIMESCALE CLOUD

Time-series data obtained from sensors does not include anything other than every-changing numerical data.

Fujitsu Develops Automatic Labeling Technology to Accelerate AI Use of Time-Series Data

Much of today's big data is time-series data, so having specific functions for time is crucial.

Don't Get Washed Out by the Overflowing Data Lake: Five Key Considerations

Time-series data is complex, explains Greg Olsen, senior vice president, products.

Using Pattern Recognition to Improve Industrial Operations

[11] Philippe esling and Carlos agon, "Time-Series Data Mining," ACM Computing Surveys, Vol.

Clustering Algorithm for Time Series with Similar Shapes

Having published a book of aggregated time-series data on the demography, economy, infrastructure, and society of the four US and six Mexican states on the border between the countries, Reich here adds a legal dimension to this quantitative overview.

The Law of the United States-Mexico Border: A Casebook

The historian product handles time-series data, as well as alarm and event data.

Brewer scales smart manufacturing platforms for next decade

Recursions legacy management action plan failed to keep pace with the large volumes of time-series data that was produced from a growing number of computer-controlled instruments capturing over 700,000 TIFF files per week.

United States : Splunk helps Recursion combine biological science with machine learning

It is commonly used to model time-series data on the attempt to explain and predict macroeconomic variables such as GDP, investment, consumption, spending, exports, imports, employment and unemployment.

MACROECONOMETRICS: STATISTICAL ALCHEMY AT THE FINAL STAGE

Manolopoulos, "Feature-based classification of time-series data," in Information Processing and Technology, M.

A Cycle Deep Belief Network Model for Multivariate Time Series Classification

Generally, there are two types of gene expression data used to predict the structure of GRNs, which are steady-state data and time-series data. The steady-state data measures the steady-state levels in different samples, while time-series data measures the expression levels at several successive time points.

Inference of Gene Regulatory Networks Using Bayesian Nonparametric Regression and Topology Information

Time-series data consists of hundreds or even thousands of measurements taken at recurring time intervals.