Research Area:  Machine Learning

Abstract:

Research on forecasting methods of time series data has become one of the hot spots. More and more time series data are produced in various fields. It provides data for the research of time series analysis method, and promotes the development of time series research. Due to the generation of highly complex and large-scale time series data, the construction of forecasting models for time series data brings greater challenges. The main challenges of time series modeling are high complexity of time series data, low accuracy and poor generalization ability of prediction model. This paper attempts to cover the existing modeling methods for time series data and classify them. In addition, we make comparisons between different methods and list some potential directions for time series forecasting.

Keywords:  

Author(s) Name:  Zhenyu Liu; Zhengtong Zhu; Jing Gao; Cheng Xu

Publisher name:  IEEE

DOI:  10.1109/ACCESS.2021.3091162

Volume Information:  Volume: 9, Page(s): 91896 - 91912, 2021

Paper Link:   https://ieeexplore.ieee.org/document/9461796