Averaging Concepts

Averaging Concepts is a methodological framework in data interpretation that systematically combines multiple data points or conceptual representations into a unified summary measure to reduce variability and highlight central tendencies.

127

Publications

6.6K

Citations

311

Authors

151

Institutions

Publications per year

2017–2026

15

Authors

311

  1. JY
    Jun Ye

    Shaoxing University, China

    5 publications · 159 citations

    5

    h-index

  2. FV
    Francesco Vasca

    University of Sannio, Italy

    3 publications · 44 citations

    3

    h-index

  3. ST
    Stephan Trenn

    University of Kaiserslautern, Germany

    3 publications · 44 citations

    3

    h-index

  4. SJ
    Susan Jo Russell

    Technical Education Research Centers, United States

    2 publications · 383 citations

    2

    h-index

  5. LJ
    L. J. Gray

    Oak Ridge National Laboratory, United States

    2 publications · 60 citations

    2

    h-index

1–5 of 311

Venues

  1. IEEE Transactions on Power Electronics

    3 publications · 474 citations

    3

    h-index

  2. SIAM Journal on Control and Optimization

    3 publications · 123 citations

    3

    h-index

  3. Journal of Intelligent & Fuzzy Systems

    2 publications · 37 citations

    2

    h-index

  4. Tamkang Journal of Mathematics

    2 publications · 42 citations

    2

    h-index

  5. 2

    h-index

1–5