Reliability Modeling Using an Adaptive Neuro-Fuzzy Inference System: Gas Turbine Application-Reference-Cited by-同舟云学术

Reliability Modeling Using an Adaptive Neuro-Fuzzy Inference System: Gas Turbine Application

Published:2021-04-03 Issue:2 Volume:13 Page:154-183
ISSN:1616-8658
Container-title:Fuzzy Information and Engineering
language:en
Short-container-title:Fuzzy Information and Engineering

Author:

Hadroug Nadji¹²,Hafaifa Ahmed¹²,Iratni Abdelhamid³,Guemana Mouloud¹⁴

Affiliation:

1. Applied Automation and Industrial Diagnostics Laboratory, Faculty of Science and Technology, University of Djelfa, Djelfa, Algeria

2. Gas Turbine Joint Research Team, University of Djelfa, Djelfa, Algeria

3. Faculty of Science and Technology, University of Bordj Bou Arreridj, El Anceur, Algeria

4. Faculty of Science and Technology, University of Medea, Medea, Algeria

Publisher

Informa UK Limited

Subject

Applied Mathematics,Artificial Intelligence,Industrial and Manufacturing Engineering,Management Science and Operations Research,Logic,Information Systems,Control and Systems Engineering,Theoretical Computer Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/16168658.2021.1915451

Reference37 articles.

1. A sequential model-based approach for gas turbine performance diagnostics

2. Fatigue reliability estimation framework for turbine rotor using multi-agent collaborative modeling

3. Vector-based deterioration index for gas turbine gas-path prognostics modeling framework

4. Uncertainty modeling in reliability analysis of floating wind turbine support structures

5. Gaussian process regression for fatigue reliability analysis of offshore wind turbines

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