Trend Features

Trend Features is a time series feature extraction method that quantifies the underlying long-term progression or directional movement in a time series by distinguishing itself from seasonal and cyclical components through the isolation of systematic, non-repeating patterns over time.

101

Publications

4.6K

Citations

348

Authors

169

Institutions

Publications per year

2017–2026

57

Authors

348

  1. SD
    Shengdong Du

    Southwest Jiaotong University, China

    5 publications · 819 citations

    5

    h-index

  2. TL
    Tianrui Li

    Southwest Jiaotong University, China

    5 publications · 819 citations

    5

    h-index

  3. WP
    Witold Pedrycz

    University of Alberta, Canada

    4 publications · 253 citations

    4

    h-index

  4. SH
    Shi‐Jinn Horng

    National Taiwan University of Science and Technology, Taiwan

    4 publications · 721 citations

    4

    h-index

  5. XG
    Xun Gong

    Southwest Jiaotong University, China

    3 publications · 302 citations

    3

    h-index

1–5 of 348

Venues

  1. IEEE Transactions on Fuzzy Systems

    TFS · 4 publications · 266 citations

    4

    h-index

  2. Expert Systems with Applications

    3 publications · 498 citations

    3

    h-index

  3. Applied Sciences

    3 publications · 138 citations

    3

    h-index

  4. arXiv (Cornell University)

    Repository · 3 publications · 126 citations

    3

    h-index

  5. IEEE Transactions on Industrial Informatics

    2 publications · 70 citations

    2

    h-index

1–5