A review on extreme learning machine
Extreme learning machine (ELM) is a training algorithm for single hidden layer feedforward
neural network (SLFN), which converges much faster than traditional methods and yields …
neural network (SLFN), which converges much faster than traditional methods and yields …
Trends in extreme learning machines: A review
Extreme learning machine (ELM) has gained increasing interest from various research fields
recently. In this review, we aim to report the current state of the theoretical research and …
recently. In this review, we aim to report the current state of the theoretical research and …
[PDF][PDF] Study of variants of extreme learning machine (ELM) brands and its performance measure on classification algorithm
JS Manoharan - Journal of Soft Computing Paradigm (JSCP), 2021 - scholar.archive.org
Recently, the feed-forward neural network is functioning with slow computation time and
increased gain. The weight vector and biases in the neural network can be tuned based on …
increased gain. The weight vector and biases in the neural network can be tuned based on …
A machine learning methodology for diagnosing chronic kidney disease
Chronic kidney disease (CKD) is a global health problem with high morbidity and mortality
rate, and it induces other diseases. Since there are no obvious symptoms during the early …
rate, and it induces other diseases. Since there are no obvious symptoms during the early …
Joint estimation of state-of-charge and state-of-health for all cells in the battery pack using “leader-follower” strategy
Developing simple and accurate state estimators for battery packs is important but
technically challenging due to not only the high number of batteries requiring monitoring but …
technically challenging due to not only the high number of batteries requiring monitoring but …
Extreme learning machine for regression and multiclass classification
Due to the simplicity of their implementations, least square support vector machine (LS-
SVM) and proximal support vector machine (PSVM) have been widely used in binary …
SVM) and proximal support vector machine (PSVM) have been widely used in binary …
Urban energy use modeling methods and tools: A review and an outlook
N Abbasabadi, M Ashayeri - Building and environment, 2019 - Elsevier
Urban energy use modeling is important for understanding and managing energy
performance in cities. However, the existing methods and tools have limitations in …
performance in cities. However, the existing methods and tools have limitations in …
Extreme learning machines: a survey
GB Huang, DH Wang, Y Lan - … journal of machine learning and cybernetics, 2011 - Springer
Computational intelligence techniques have been used in wide applications. Out of
numerous computational intelligence techniques, neural networks and support vector …
numerous computational intelligence techniques, neural networks and support vector …
Extreme learning machine: algorithm, theory and applications
S Ding, H Zhao, Y Zhang, X Xu, R Nie - Artificial Intelligence Review, 2015 - Springer
Extreme learning machine (ELM) is a new learning algorithm for the single hidden layer
feedforward neural networks. Compared with the conventional neural network learning …
feedforward neural networks. Compared with the conventional neural network learning …
Landslide displacement prediction based on multivariate chaotic model and extreme learning machine
This paper proposes a multivariate chaotic Extreme Learning Machine (ELM) model for the
prediction of the displacement of reservoir landslides. The displacement time series of the …
prediction of the displacement of reservoir landslides. The displacement time series of the …