应用时间序列分析

时间序列-应用 (Time Series - Applications)

We discussed time series analysis in this tutorial, which has given us the understanding that time series models first recognize the trend and seasonality from the existing observations and then forecast a value based on this trend and seasonality. Such analysis is useful in various fields such as −

我们在本教程中讨论了时间序列分析，这使我们理解了时间序列模型首先会从现有观察值中识别趋势和季节性，然后根据该趋势和季节性预测值。 这种分析在各个领域都非常有用，例如-

• Financial Analysis − It includes sales forecasting, inventory analysis, stock market analysis, price estimation.

  财务分析 -包括销售预测，库存分析，股票市场分析，价格估计。

• Weather Analysis − It includes temperature estimation, climate change, seasonal shift recognition, weather forecasting.

  天气分析 -包括温度估计，气候变化，季节性变化识别，天气预报。

• Network Data Analysis − It includes network usage prediction, anomaly or intrusion detection, predictive maintenance.

  网络数据分析 -它包括网络使用情况预测，异常或入侵检测，预测性维护。

• Healthcare Analysis − It includes census prediction, insurance benefits prediction, patient monitoring.

  医疗保健分析 -它包括人口普查预测，保险利益预测，患者监测。

翻译自: https://www.tutorialspoint.com/time_series/time_series_applications.htm

应用时间序列分析