Similarity-based Forecasting

Similarity-Based Forecasting is a demand forecasting method that leverages historical data from analogous products or markets to predict new product demand by identifying and exploiting patterns of similarity in their performance trajectories.

49

Publications

2K

Citations

152

Authors

83

Institutions

Publications per year

2017–2026

29

Variants

Similarity-based Demand Forecasting

Authors

152

  1. FM
    Francisco Martínez‐Álvarez

    Universidad Pablo de Olavide, Spain

    4 publications · 394 citations

    4

    h-index

  2. AT
    Alicia Troncoso

    Universidad Pablo de Olavide, Spain

    3 publications · 369 citations

    3

    h-index

  3. SC
    Shyi‐Ming Chen

    National Taiwan University of Science and Technology, Taiwan

    3 publications · 358 citations

    3

    h-index

  4. WJ
    Wen‐Shan Jian

    Taipei Medical University, Taiwan

    3 publications · 358 citations

    3

    h-index

  5. SC
    Shou-Hsiung Cheng

    Chienkuo Technology University, Taiwan

    2 publications · 230 citations

    2

    h-index

1–5 of 152

Venues

  1. IEEE Access

    5 publications · 164 citations

    5

    h-index

  2. Information Sciences

    3 publications · 397 citations

    3

    h-index

  3. Energies

    3 publications · 51 citations

    3

    h-index

  4. Expert Systems with Applications

    2 publications · 87 citations

    2

    h-index

  5. Eastern-European Journal of Enterprise Technologies

    EEJET · 2 publications · 62 citations

    2

    h-index

1–5