首页|时间序列预测模型发展趋势分析

时间序列预测模型发展趋势分析

扫码查看
时间序列预测是当前研究的主要方向之一,能有效解决工业、交通等领域的工艺指标和客流量预测问题.通过分析现有的时间序列模型,可以预测未来的发展趋势.首先,分析现有时间序列预测模型的结构,以了解其技术实现方式;其次,根据技术手段的不同,将模型分为优化提升类和创新类;最后,讨论了时间序列预测模型的未来发展趋势.
Analysis of the Development Trends of Time Series Forecasting Models
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.

Time seriesOptimization and improvementNeural networkTime Series Forecasting model

王瑞芳、马平安、俞婷

展开 >

兰州资源环境职业技术大学 甘肃兰州 730021

时间序列 优化提升 神经网络 时间序列预测模型

2023年度校级职业教育教学改革研究项目

JG2023044

2024

科技资讯
北京国际科技服务中心 北京合作创新国际科技服务中心

科技资讯

影响因子:0.51
ISSN:1672-3791
年,卷(期):2024.22(19)
  • 1