Autonomous learning for fuzzy systems: a review

X Gu, J Han, Q Shen, PP Angelov - Artificial Intelligence Review, 2023‏ - Springer
As one of the three pillars in computational intelligence, fuzzy systems are a powerful
mathematical tool widely used for modelling nonlinear problems with uncertainties. Fuzzy …

Revisiting evolutionary fuzzy systems: Taxonomy, applications, new trends and challenges

A Fernandez, V Lopez, MJ del Jesus… - Knowledge-Based Systems, 2015‏ - Elsevier
Abstract Evolutionary Fuzzy Systems are a successful hybridization between fuzzy systems
and Evolutionary Algorithms. They integrate both the management of imprecision …

A deep learning approach for anomaly detection based on SAE and LSTM in mechanical equipment

Z Li, J Li, Y Wang, K Wang - The International Journal of Advanced …, 2019‏ - Springer
Anomaly in mechanical systems may cause equipment to break down with serious safety,
environment, and economic impact. Since many mechanical equipment usually operates …

Multi-sensor information fusion for remaining useful life prediction of machining tools by adaptive network based fuzzy inference system

J Wu, Y Su, Y Cheng, X Shao, C Deng, C Liu - Applied Soft Computing, 2018‏ - Elsevier
Remaining useful life (RUL) prediction of machining tools is a typical multi-sensor
information fusion problem. It involves the use of the monitoring information acquired from …

Dimensionality reduce-based for remaining useful life prediction of machining tools with multisensor fusion

Y Zhu, J Wu, J Wu, S Liu - Reliability Engineering & System Safety, 2022‏ - Elsevier
The remaining useful life (RUL) prediction has received increasing research attention in
recent years due to its essential role in improving industrial manufacturing systems' …

Comparison of four direct classification methods for intelligent fault diagnosis of rotating machinery

D Dou, S Zhou - Applied Soft Computing, 2016‏ - Elsevier
Condition monitoring of rotating machinery is important to promptly detect early faults,
identify potential problems, and prevent complete failure. Four direct classification methods …

Online active learning in data stream regression using uncertainty sampling based on evolving generalized fuzzy models

E Lughofer, M Pratama - IEEE Transactions on fuzzy systems, 2017‏ - ieeexplore.ieee.org
In this paper, we propose three criteria for efficient sample selection in case of data stream
regression problems within an online active learning context. The selection becomes …

Fully unsupervised fault detection and identification based on recursive density estimation and self-evolving cloud-based classifier

BSJ Costa, PP Angelov, LA Guedes - Neurocomputing, 2015‏ - Elsevier
In this paper, we propose a two-stage algorithm for real-time fault detection and identification
of industrial plants. Our proposal is based on the analysis of selected features using …

Prediction and analysis of cold rolling mill vibration based on a data-driven method

X Lu, J Sun, Z Song, G Li, Z Wang, Y Hu, Q Wang… - Applied Soft …, 2020‏ - Elsevier
Mill chatter is one of the most common problems in cold rolling. Thus, it is important to
investigate the mill chatter phenomenon to ensure a high-speed and stable rolling process …

An evolving approach to unsupervised and real-time fault detection in industrial processes

CG Bezerra, BSJ Costa, LA Guedes… - Expert systems with …, 2016‏ - Elsevier
Fault detection in industrial processes is a field of application that has gaining considerable
attention in the past few years, resulting in a large variety of techniques and methodologies …