InfoWorld

An introduction to time series forecasting

Time series forecasts are used to predict a future value or a classification at a particular point in time. Here’s a brief overview of their common uses and how they are developed. Industries from ...
Visual Studio Magazine

Neural Network Time Series Regression Using Python

The goal of a time series regression problem is best explained by a concrete example. Suppose you own an airline company and you want to predict the number of passengers you'll have next month based ...
EurekAlert!

Hybrid quantum-classical algorithm accelerates dynamic mode decomposition for high-dimensional time series analysis

Seeking to reduce the computing power needed for the widely used dynamic mode decomposition algorithm, a team of researchers in China led by Guo-Ping Guo developed a quantum-classical hybrid algorithm ...
ascopubs.org

Time Series Prediction of Lung Cancer Death Rates on the Basis of SEER Data

This study used SEER data from 1975 to 2018 and included 545,486 patients with lung cancer. The best parameters for ARIMA are ARIMA (p, d, q) = (0, 2, 2). In addition, the best parameter for SES was α ...
InfoWorld

The value of time series data and TSDBs

Time series data key insights in domains ranging from science and medicine to systems monitoring and industrial IoT. Understand time series data and the databases designed to ingest, store, and ...