A review of data-driven machinery fault diagnosis using machine learning algorithms
J Cen, Z Yang, X Liu, J Xiong, H Chen - Journal of Vibration Engineering & …, 2022 - Springer
Purpose This article aims to systematically review the recent research advances in data-
driven machinery fault diagnosis based on machine learning algorithms, and provide …
driven machinery fault diagnosis based on machine learning algorithms, and provide …
Machine learning for fault analysis in rotating machinery: A comprehensive review
As the concept of Industry 4.0 is introduced, artificial intelligence-based fault analysis is
attracted the corresponding community to develop effective intelligent fault diagnosis and …
attracted the corresponding community to develop effective intelligent fault diagnosis and …
[HTML][HTML] Towards extraction of orthogonal and parsimonious non-linear modes from turbulent flows
Modal-decomposition techniques are computational frameworks based on data aimed at
identifying a low-dimensional space for capturing dominant flow features: the so-called …
identifying a low-dimensional space for capturing dominant flow features: the so-called …
Using enhanced crow search algorithm optimization-extreme learning machine model to forecast short-term wind power
LL Li, ZF Liu, ML Tseng, K Jantarakolica… - Expert Systems with …, 2021 - Elsevier
The strong volatility and randomness of wind power impact the grid and reduce the voltage
quality of the grid when wind power is connected to the grid in large scale. The power sector …
quality of the grid when wind power is connected to the grid in large scale. The power sector …
Research on fault diagnosis of gas turbine rotor based on adversarial discriminative domain adaption transfer learning
S Liu, H Wang, J Tang, X Zhang - Measurement, 2022 - Elsevier
In the process of gas turbine rotor fault diagnosis based on data-driven, transfer learning is
an effective method to solve the lack of gas turbines labeled data, which will result in domain …
an effective method to solve the lack of gas turbines labeled data, which will result in domain …
Recognition of DDoS attacks on SD-VANET based on combination of hyperparameter optimization and feature selection
Abstract The aim of Vehicular Ad Hoc Networks (VANETs) is to provide drivers and
passengers with various applications and services for comfortable transportation by …
passengers with various applications and services for comfortable transportation by …
Intelligent mix design of recycled brick aggregate concrete based on swarm intelligence
The mechanical properties of recycled brick aggregate concrete (RBAC) are significantly
affected by design parameters such as recycled brick aggregate (RBA) replacement ratio …
affected by design parameters such as recycled brick aggregate (RBA) replacement ratio …
ACO-KELM: anti coronavirus optimized kernel-based softplus extreme learning machine for classification of skin cancer
N Liu, MR Rejeesh, V Sundararaj… - Expert Systems with …, 2023 - Elsevier
Due to the presence of redundant and irrelevant features in large-dimensional biomedical
datasets, the prediction accuracy of disease diagnosis can often be decreased. Therefore, it …
datasets, the prediction accuracy of disease diagnosis can often be decreased. Therefore, it …
Advances in fault detection and diagnosis for thermal power plants: A review of intelligent techniques
Thermal power plants (TPPs) are critical to supplying energy to society, and ensuring their
safe and efficient operation is a top priority. To minimize maintenance shutdowns and costs …
safe and efficient operation is a top priority. To minimize maintenance shutdowns and costs …
[HTML][HTML] Influence of personality and modality on peer assessment evaluation perceptions using Machine Learning techniques
The successful instructional design of self and peer assessment in higher education poses
several challenges that instructors need to be aware of. One of these is the influence of …
several challenges that instructors need to be aware of. One of these is the influence of …