Deep learning for air pollutant concentration prediction: A review
Air pollution has become one of the critical environmental problem in the 21st century and
has attracted worldwide attentions. To mitigate it, many researchers have investigated the …
has attracted worldwide attentions. To mitigate it, many researchers have investigated the …
Randomness in neural networks: an overview
Neural networks, as powerful tools for data mining and knowledge engineering, can learn
from data to build feature‐based classifiers and nonlinear predictive models. Training neural …
from data to build feature‐based classifiers and nonlinear predictive models. Training neural …
Design of deep echo state networks
In this paper, we provide a novel approach to the architectural design of deep Recurrent
Neural Networks using signal frequency analysis. In particular, focusing on the Reservoir …
Neural Networks using signal frequency analysis. In particular, focusing on the Reservoir …
The challenges of modern computing and new opportunities for optics
In recent years, the explosive development of artificial intelligence implementing by artificial
neural networks (ANNs) creates inconceivable demands for computing hardware. However …
neural networks (ANNs) creates inconceivable demands for computing hardware. However …
Reservoir computing approaches for representation and classification of multivariate time series
Classification of multivariate time series (MTS) has been tackled with a large variety of
methodologies and applied to a wide range of scenarios. Reservoir computing (RC) …
methodologies and applied to a wide range of scenarios. Reservoir computing (RC) …
A novel compound fault-tolerant method based on online sequential extreme learning machine with cycle reservoir for turbofan engine direct thrust control
X Zhou, J Huang, F Lu, W Zhou, P Liu - Aerospace Science and …, 2023 - Elsevier
Sensors are the primary information source of the aeroengine control system, their
measurement accuracy is closely related to whether the engine can operate safely and …
measurement accuracy is closely related to whether the engine can operate safely and …
A unified framework for reservoir computing and extreme learning machines based on a single time-delayed neuron
In this paper we present a unified framework for extreme learning machines and reservoir
computing (echo state networks), which can be physically implemented using a single …
computing (echo state networks), which can be physically implemented using a single …
Wind turbine gearbox fault diagnosis based on multi-sensor signals fusion
Y Zhao, Z Song, D Li, R Qian… - Protection and Control of …, 2024 - ieeexplore.ieee.org
This paper proposes a novel fault diagnosis method by fusing the information from multi-
sensor signals to improve the reliability of the conventional vibration-based wind turbine …
sensor signals to improve the reliability of the conventional vibration-based wind turbine …
Investigating echo-state networks dynamics by means of recurrence analysis
In this paper, we elaborate over the well-known interpretability issue in echo-state networks
(ESNs). The idea is to investigate the dynamics of reservoir neurons with time-series …
(ESNs). The idea is to investigate the dynamics of reservoir neurons with time-series …
Multiobjective learning in the model space for time series classification
A well-defined distance is critical for the performance of time series classification. Existing
distance measurements can be categorized into two branches. One is to utilize handmade …
distance measurements can be categorized into two branches. One is to utilize handmade …