A review on soft sensors for monitoring, control, and optimization of industrial processes
Over the past twenty years, numerous research outcomes have been published, related to
the design and implementation of soft sensors. In modern industrial processes, various types …
the design and implementation of soft sensors. In modern industrial processes, various types …
Learning under concept drift: A review
Concept drift describes unforeseeable changes in the underlying distribution of streaming
data overtime. Concept drift research involves the development of methodologies and …
data overtime. Concept drift research involves the development of methodologies and …
A two-stage method based on extreme learning machine for predicting the remaining useful life of rolling-element bearings
Z Pan, Z Meng, Z Chen, W Gao, Y Shi - Mechanical Systems and Signal …, 2020 - Elsevier
Rolling-element bearing is one of the main parts of rotating equipment. In order to avoid the
mechanical equipment damage caused by the sudden failure of rolling-element bearings, it …
mechanical equipment damage caused by the sudden failure of rolling-element bearings, it …
Enhanced ensemble structures using wavelet neural networks applied to short-term load forecasting
Load forecasting implies directly in financial return and information for electrical systems
planning. A framework to build wavenet ensemble for short-term load forecasting is …
planning. A framework to build wavenet ensemble for short-term load forecasting is …
A novel wind speed forecasting based on hybrid decomposition and online sequential outlier robust extreme learning machine
D Zhang, X Peng, K Pan, Y Liu - Energy conversion and management, 2019 - Elsevier
As the wind energy developing, wind speed prediction is important for the reliability of wind
power system and the integration of wind energy into the power network. This paper …
power system and the integration of wind energy into the power network. This paper …
Volatility forecasting of crude oil futures based on a genetic algorithm regularization online extreme learning machine with a forgetting factor: The role of news during …
F Weng, H Zhang, C Yang - Resources Policy, 2021 - Elsevier
The outbreak of news and opinions during the COVID-19 pandemic is unprecedented in this
age of rapid dissemination of information. The ensuing uncertainty has led to the emergence …
age of rapid dissemination of information. The ensuing uncertainty has led to the emergence …
Neural network-based flight control systems: Present and future
As the first review in this field, this paper presents an in-depth mathematical view of
Intelligent Flight Control Systems (IFCSs), particularly those based on artificial neural …
Intelligent Flight Control Systems (IFCSs), particularly those based on artificial neural …
A hybrid approach to motion prediction for ship docking—Integration of a neural network model into the ship dynamic model
While automatic controllers are frequently used during transit operations and low-speed
maneuvering of ships, ship operators typically perform docking maneuvers. This task is more …
maneuvering of ships, ship operators typically perform docking maneuvers. This task is more …
A neural network-based on-device learning anomaly detector for edge devices
Semi-supervised anomaly detection is an approach to identify anomalies by learning the
distribution of normal data. Backpropagation neural networks (ie, BP-NNs) based …
distribution of normal data. Backpropagation neural networks (ie, BP-NNs) based …
Ensemble of optimized echo state networks for remaining useful life prediction
Abstract The use of Echo State Networks (ESNs) for the prediction of the Remaining Useful
Life (RUL) of industrial components, ie the time left before the equipment will stop fulfilling its …
Life (RUL) of industrial components, ie the time left before the equipment will stop fulfilling its …