Time Series 简明教程

Time Series - Introduction

时间序列是某段时间内一系列的观察结果。单变量时间序列由一个变量在一段时间内按周期性时间实例获取的值组成，而多变量时间序列由多个变量在一段时间内在同一周期性时间实例获取的值组成。我们所有人每天都会遇到的最简单的时间序列示例是全天或全周或全月或全年的温度变化。

A time series is a sequence of observations over a certain period. A univariate time series consists of the values taken by a single variable at periodic time instances over a period, and a multivariate time series consists of the values taken by multiple variables at the same periodic time instances over a period. The simplest example of a time series that all of us come across on a day to day basis is the change in temperature throughout the day or week or month or year.

时间数据分析能够让我们深入了解一个变量如何随时间变化，或者它如何依赖其他变量值的改变。变量与其之前的值和/或其他变量之间的这种关系可以分析时间序列预测并在人工智能中得到众多应用。

The analysis of temporal data is capable of giving us useful insights on how a variable changes over time, or how it depends on the change in the values of other variable(s). This relationship of a variable on its previous values and/or other variables can be analyzed for time series forecasting and has numerous applications in artificial intelligence.