Fast and accurate classification of time series data using extended ELM: Application in fault diagnosis of air handling units
The extreme learning machine (ELM) is famous for its single hidden-layer feed-forward
neural network which results in much faster learning speed comparing with traditional …
neural network which results in much faster learning speed comparing with traditional …
Orthogonal incremental extreme learning machine for regression and multiclass classification
L Ying - Neural computing and applications, 2016 - Springer
Single-hidden-layer feedforward networks with randomly generated additive or radial basis
function hidden nodes have been theoretically proved that they can approximate any …
function hidden nodes have been theoretically proved that they can approximate any …
Multilayer one-class extreme learning machine
One-class classification has been found attractive in many applications for its effectiveness
in anomaly or outlier detection. Representative one-class classification algorithms include …
in anomaly or outlier detection. Representative one-class classification algorithms include …
An improved algorithm for incremental extreme learning machine
S Song, M Wang, Y Lin - Systems science & control engineering, 2020 - Taylor & Francis
Incremental extreme learning machine (I-ELM) randomly obtains the input weights and the
hidden layer neuron bias during the training process. Some hidden nodes in the ELM play a …
hidden layer neuron bias during the training process. Some hidden nodes in the ELM play a …
Extreme learning machine and its applications
S Ding, X Xu, R Nie - Neural Computing and Applications, 2014 - Springer
Recently, a novel learning algorithm for single-hidden-layer feedforward neural networks
(SLFNs) named extreme learning machine (ELM) was proposed by Huang et al. The …
(SLFNs) named extreme learning machine (ELM) was proposed by Huang et al. The …
Weighted extreme learning machine for imbalance learning
Extreme learning machine (ELM) is a competitive machine learning technique, which is
simple in theory and fast in implementation. The network types are “generalized” single …
simple in theory and fast in implementation. The network types are “generalized” single …
Regression and classification using extreme learning machine based on L1-norm and L2-norm
X Luo, X Chang, X Ban - Neurocomputing, 2016 - Elsevier
Extreme learning machine (ELM) is a very simple machine learning algorithm and it can
achieve a good generalization performance with extremely fast speed. Therefore it has …
achieve a good generalization performance with extremely fast speed. Therefore it has …
Ensemble based extreme learning machine
Extreme learning machine (ELM) was proposed as a new class of learning algorithm for
single-hidden layer feedforward neural network (SLFN). To achieve good generalization …
single-hidden layer feedforward neural network (SLFN). To achieve good generalization …
Improving classification performance through an advanced ensemble based heterogeneous extreme learning machines
AOM Abuassba, D Zhang, X Luo… - Computational …, 2017 - Wiley Online Library
Extreme Learning Machine (ELM) is a fast‐learning algorithm for a single‐hidden layer
feedforward neural network (SLFN). It often has good generalization performance. However …
feedforward neural network (SLFN). It often has good generalization performance. However …
Low complexity adaptive forgetting factor for online sequential extreme learning machine (OS-ELM) for application to nonstationary system estimations
J Lim, S Lee, HS Pang - Neural Computing and Applications, 2013 - Springer
Abstract Huang et al.(2004) has recently proposed an on-line sequential ELM (OS-ELM) that
enables the extreme learning machine (ELM) to train data one-by-one as well as chunk-by …
enables the extreme learning machine (ELM) to train data one-by-one as well as chunk-by …