Scalability, Explainability and Performance of Data-Driven Algorithms in Predicting the Remaining Useful Life: A Comprehensive Review-Reference-Cited by-同舟云学术

Scalability, Explainability and Performance of Data-Driven Algorithms in Predicting the Remaining Useful Life: A Comprehensive Review

Published:2023 Issue: Volume:11 Page:41741-41769
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Ramezani Somayeh Bakhtiari¹^ORCID,Cummins Logan¹^ORCID,Killen Brad¹,Carley Richard²,Amirlatifi Amin³^ORCID,Rahimi Shahram¹,Seale Maria⁴^ORCID,Bian Linkan⁵^ORCID

Affiliation:

1. Department of Computer Science and Engineering, Mississippi State University, Starkville, MS, USA

2. Institute for Systems Engineering Research, Mississippi State University, Vicksburg, MS, USA

3. Dave C. Swalm School of Chemical Engineering, Mississippi State University, Starkville, MS, USA

4. U.S. Army Engineer Research and Development Center (ERDC), Vicksburg, MS, USA

5. Department of Industrial and Systems Engineering, Mississippi State University, Starkville, MS, USA

Funder

U.S. Department of Defense (DoD) High Performance Computing Modernization Program, Mississippi State University, through the U.S. Army Engineering Research and Develop Center

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

https://ieeexplore.ieee.org/ielam/6287639/10005208/10103701-aam.pdf

Reference279 articles.

1. Echo state network

2. The particle swarm optimization multi-kernel relevance vector machine for remaining useful life prediction of lithium-ion batteries

3. Remaining useful life estimation via transformer encoder enhanced by a gated convolutional unit

4. Real-Time Updating High-Order Extended Kalman Filtering Method Based on Fixed-Step Life Prediction for Vehicle Lithium-Ion Batteries

5. Generative adversarial networks;goodfellow;Proc Neural Inf Process Syst (NIPS) Conf,2014

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