Neural Network Diagnostics

Neural Network Diagnostics is a computational framework within engine diagnostics that employs machine learning models to identify, analyze, and interpret anomalies or faults in engine performance by leveraging the pattern recognition capabilities of artificial neural networks.

820

Publications

44.2K

Citations

2.5K

Authors

798

Institutions

Publications per year

2017–2026

350

Authors

2.5K

  1. RU
    R.E. Uhrig

    University of Tennessee at Knoxville, United States

    8 publications · 404 citations

    8

    h-index

  2. SD
    Stanisław Duer

    Koszalin University of Technology, Poland

    7 publications · 179 citations

    7

    h-index

  3. KK
    K. Khorasani

    Concordia University, Canada

    7 publications · 819 citations

    7

    h-index

  4. GF
    G. Franceschini

    University of Parma, Italy

    6 publications · 404 citations

    6

    h-index

  5. KM
    K. Mathioudakis

    National Technical University of Athens, Greece

    6 publications · 221 citations

    6

    h-index

1–5 of 2.5K

Venues

  1. 18

    h-index

  2. Measurement

    20 publications · 1.6K citations

    18

    h-index

  3. Expert Systems with Applications

    19 publications · 1.6K citations

    16

    h-index

  4. Sensors

    14 publications · 511 citations

    13

    h-index

  5. Mechanical Systems and Signal Processing

    MSSP · 12 publications · 2.2K citations

    12

    h-index

1–5