Multi-scale Forecasting

Multi-Scale Forecasting is a forecasting framework that integrates data and models across multiple temporal and spatial scales to capture both local dynamics and global patterns, distinguishing it from single-scale approaches by explicitly accounting for scale-dependent interactions and hierarchies within complex systems.

50

Publications

3K

Citations

326

Authors

179

Institutions

Publications per year

2017–2026

34

Authors

326

  1. LT
    Ling Tang

    Beijing University of Chemical Technology, China

    3 publications · 308 citations

    3

    h-index

  2. SW
    Shouyang Wang

    Chinese Academy of Sciences, China

    2 publications · 107 citations

    2

    h-index

  3. XL
    Xinggao Liu

    State Key Laboratory of Industrial Control Technology

    2 publications · 59 citations

    2

    h-index

  4. HC
    Huayou Chen

    Anhui University, China

    1 publications · 119 citations

    1

    h-index

  5. BW
    Bo Wen

    Alibaba Group (China), China

    1 publications · 210 citations

    1

    h-index

1–5 of 326

Venues

  1. IEEE Access

    3 publications · 101 citations

    3

    h-index

  2. Energy

    3 publications · 180 citations

    3

    h-index

  3. Expert Systems with Applications

    2 publications · 161 citations

    2

    h-index

  4. Applied Energy

    2 publications · 174 citations

    2

    h-index

  5. arXiv (Cornell University)

    Repository · 2 publications · 126 citations

    2

    h-index

1–5