Simple Exponential Smoothing

Simple Exponential Smoothing is a time series forecasting method that belongs to the class of exponential smoothing techniques, distinguished by its use of a single smoothing parameter to exponentially weighted past observations for estimating the level component in data without trend or seasonal patterns.

83

Publications

4.9K

Citations

219

Authors

144

Institutions

Publications per year

2017–2026

41

Variants

Ses

Authors

219

  1. ES
    Everette S. Gardner

    University of Houston, United States

    3 publications · 173 citations

    3

    h-index

  2. SS
    Sima Siami‐Namini

    Texas Tech University, United States

    2 publications · 1.3K citations

    2

    h-index

  3. AS
    Akbar Siami Namin

    Texas Tech University, United States

    2 publications · 1.3K citations

    2

    h-index

  4. MN
    Mohammad Nayeem Hasan

    Shahjalal University of Science and Technology, Bangladesh

    2 publications · 108 citations

    2

    h-index

  5. WH
    Walayat Hussain

    University of Technology Sydney, Australia

    2 publications · 64 citations

    2

    h-index

1–5 of 219

Venues

  1. International Journal of Production Research

    3 publications · 96 citations

    3

    h-index

  2. Management Science

    3 publications · 213 citations

    3

    h-index

  3. Journal of Forecasting

    3 publications · 131 citations

    3

    h-index

  4. 2

    h-index

  5. Journal of the Operational Research Society

    OR · 2 publications · 37 citations

    2

    h-index

1–5