A Review of multilayer extreme learning machine neural networks

JA Vásquez-Coronel, M Mora, K Vilches - Artificial Intelligence Review, 2023‏ - Springer
Abstract The Extreme Learning Machine is a single-hidden-layer feedforward learning
algorithm, which has been successfully applied in regression and classification problems in …

Remote sensing: an advanced technique for crop condition assessment

K Ennouri, A Kallel - Mathematical Problems in Engineering, 2019‏ - Wiley Online Library
Actually, cultivators are increasingly arranging innovative high technical and scientific
estimations in the aim to enhance agricultural sustainability, effectiveness, and/or plant …

Artificial intelligence enabled efficient power generation and emissions reduction underpinning net-zero goal from the coal-based power plants

WM Ashraf, GM Uddin, HA Ahmad, MA Jamil… - Energy Conversion and …, 2022‏ - Elsevier
A large power generation facility is a complex multi-criteria system associated with
multivariate couplings, high dependency, and non-linearity among the operating variables …

Extreme learning machine and adaptive sparse representation for image classification

J Cao, K Zhang, M Luo, C Yin, X Lai - Neural networks, 2016‏ - Elsevier
Recent research has shown the speed advantage of extreme learning machine (ELM) and
the accuracy advantage of sparse representation classification (SRC) in the area of image …

Inverse-free extreme learning machine with optimal information updating

S Li, ZH You, H Guo, X Luo… - IEEE transactions on …, 2015‏ - ieeexplore.ieee.org
The extreme learning machine (ELM) has drawn insensitive research attentions due to its
effectiveness in solving many machine learning problems. However, the matrix inversion …

Regularized label relaxation linear regression

X Fang, Y Xu, X Li, Z Lai, WK Wong… - IEEE transactions on …, 2017‏ - ieeexplore.ieee.org
Linear regression (LR) and some of its variants have been widely used for classification
problems. Most of these methods assume that during the learning phase, the training …

Multilayer extreme learning machine with subnetwork nodes for representation learning

Y Yang, QMJ Wu - IEEE transactions on cybernetics, 2015‏ - ieeexplore.ieee.org
The extreme learning machine (ELM), which was originally proposed for “generalized”
single-hidden layer feedforward neural networks, provides efficient unified learning …

Two-hidden-layer extreme learning machine for regression and classification

BY Qu, BF Lang, JJ Liang, AK Qin, OD Crisalle - Neurocomputing, 2016‏ - Elsevier
As a single-hidden-layer feedforward neural network, an extreme learning machine (ELM)
randomizes the weights between the input layer and the hidden layer as well as the bias of …

An extreme learning machine model for geosynthetic-reinforced sandy soil foundations

MNA Raja, SK Shukla - Proceedings of the institution of civil …, 2022‏ - icevirtuallibrary.com
In the past, several experimental and theoretical studies have been carried out to evaluate
the ultimate bearing capacity (UBC) of geosynthetic-reinforced sandy soil foundations …

Excavation equipment recognition based on novel acoustic statistical features

J Cao, W Wang, J Wang, R Wang - IEEE Transactions on …, 2016‏ - ieeexplore.ieee.org
Excavation equipment recognition attracts increasing attentions in recent years due to its
significance in underground pipeline network protection and civil construction management …