Time series forecasting is one of the primary research directions currently.It can effectively addresses is-sues such as process indicators and passenger flow forecasting in fields like industry and transportation.Future devel-opment trends can be forecasted by analyzing the existing time series models.Firstly,an analysis of the structure of existing Time Series Forecasting models is conducted to identify their technical implementation methods.Then,based on different technical approaches,they are classified into optimization-enhancement and innovation catego-ries.Finally,the future development trends of time series forecasting models are discussed.
关键词
时间序列/优化提升/神经网络/时间序列预测模型
Key words
Time series/Optimization and improvement/Neural network/Time Series Forecasting model
维普
万方数据