Support vector machine in structural reliability analysis: A review
A Roy, S Chakraborty - Reliability Engineering & System Safety, 2023 - Elsevier
Support vector machine (SVM) is a powerful machine learning technique relying on the
structural risk minimization principle. The applications of SVM in structural reliability analysis …
structural risk minimization principle. The applications of SVM in structural reliability analysis …
Machine learning for structural engineering: A state-of-the-art review
HT Thai - Structures, 2022 - Elsevier
Abstract Machine learning (ML) has become the most successful branch of artificial
intelligence (AI). It provides a unique opportunity to make structural engineering more …
intelligence (AI). It provides a unique opportunity to make structural engineering more …
Physics-informed machine learning for reliability and systems safety applications: State of the art and challenges
The computerized simulations of physical and socio-economic systems have proliferated in
the past decade, at the same time, the capability to develop high-fidelity system predictive …
the past decade, at the same time, the capability to develop high-fidelity system predictive …
Machine learning-based methods in structural reliability analysis: A review
Structural Reliability analysis (SRA) is one of the prominent fields in civil and mechanical
engineering. However, an accurate SRA in most cases deals with complex and costly …
engineering. However, an accurate SRA in most cases deals with complex and costly …
Deep imbalanced domain adaptation for transfer learning fault diagnosis of bearings under multiple working conditions
The tremendous success of deep learning and transfer learning broadened the scope of
fault diagnosis, especially the latter further improved the diagnosis accuracy under multiple …
fault diagnosis, especially the latter further improved the diagnosis accuracy under multiple …
Attention-based deep meta-transfer learning for few-shot fine-grained fault diagnosis
Deep learning-based fault diagnosis methods have made tremendous progress in recent
years; however, most of these methods are coarse grained and data demanding that cannot …
years; however, most of these methods are coarse grained and data demanding that cannot …
Prognostics and health management: A review from the perspectives of design, development and decision
Prognostics and health management (PHM) is an enabling technology used to maintain the
reliable, efficient, economic and safe operation of engineering equipment, systems and …
reliable, efficient, economic and safe operation of engineering equipment, systems and …
Aircraft engine remaining useful life estimation via a double attention-based data-driven architecture
L Liu, X Song, Z Zhou - Reliability Engineering & System Safety, 2022 - Elsevier
Remaining useful life (RUL) estimation has been intensively studied, given its important role
in prognostics and health management (PHM) of industry. Recently, data-driven structures …
in prognostics and health management (PHM) of industry. Recently, data-driven structures …
Intelligent fault identification of hydraulic pump using deep adaptive normalized CNN and synchrosqueezed wavelet transform
S Tang, Y Zhu, S Yuan - Reliability Engineering & System Safety, 2022 - Elsevier
Hydraulic piston pump is known as one of the most critical parts in a typical hydraulic
transmission system. It is imperative to probe into an accurate fault diagnosis method to …
transmission system. It is imperative to probe into an accurate fault diagnosis method to …
Explainable artificial intelligence (xai) for intrusion detection and mitigation in intelligent connected vehicles: A review
The potential for an intelligent transportation system (ITS) has been made possible by the
growth of the Internet of things (IoT) and artificial intelligence (AI), resulting in the integration …
growth of the Internet of things (IoT) and artificial intelligence (AI), resulting in the integration …