Investigation of fault detection and isolation accuracy of different Machine learning techniques with different data processing methods for gas turbine
Classification is an essential task for many applications, including text classification, image classification, data classification, and so on. The present study investigates the accuracy of different machine learning classification algorithms with three different data smoothing techniques for gas t...
Saved in:
Main Authors: | Molla Salilew, W., Ambri Abdul Karim, Z., Alemu Lemma, T. |
---|---|
Format: | Article |
Published: |
Elsevier B.V.
2022
|
Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133405683&doi=10.1016%2fj.aej.2022.06.026&partnerID=40&md5=5592a5b7b2809a9d6a23372fce456819 http://eprints.utp.edu.my/33296/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Investigation of fault detection and isolation accuracy of different Machine learning techniques with different data processing methods for gas turbine
by: Molla Salilew, W., et al.
Published: (2022) -
Simultaneous Fault Diagnostics for Three-Shaft Industrial Gas Turbine
by: Salilew, Waleligne Molla, et al.
Published: (2023) -
Synergistic Effect of Physical Faults and Variable Inlet Guide Vane Drift on Gas Turbine Engine
by: Salilew, Waleligne Molla, et al.
Published: (2023) -
Wavelet Neural Network based Fault Detection and Diagnosis in an Industrial Gas Turbine
by: Alemu Lemma, Tamiru, et al.
Published: (2011) -
Fault Detection Relevant Modeling of an Industrial Gas Turbine based on Neuro-Fuzzy Approach
by: Alemu Lemma, Tamiru, et al.
Published: (2010)