A review on extreme learning machine

J Wang, S Lu, SH Wang, YD Zhang - Multimedia Tools and Applications, 2022‏ - Springer
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 …

A review on neural networks with random weights

W Cao, X Wang, Z Ming, J Gao - Neurocomputing, 2018‏ - Elsevier
In big data fields, with increasing computing capability, artificial neural networks have shown
great strength in solving data classification and regression problems. The traditional training …

Metaheuristic design of feedforward neural networks: A review of two decades of research

VK Ojha, A Abraham, V Snášel - Engineering Applications of Artificial …, 2017‏ - Elsevier
Over the past two decades, the feedforward neural network (FNN) optimization has been a
key interest among the researchers and practitioners of multiple disciplines. The FNN …

Extreme learning machine for multilayer perceptron

J Tang, C Deng, GB Huang - IEEE transactions on neural …, 2015‏ - ieeexplore.ieee.org
Extreme learning machine (ELM) is an emerging learning algorithm for the generalized
single hidden layer feedforward neural networks, of which the hidden node parameters are …

A review of machine learning for near-infrared spectroscopy

W Zhang, LC Kasun, QJ Wang, Y Zheng, Z Lin - Sensors, 2022‏ - mdpi.com
The analysis of infrared spectroscopy of substances is a non-invasive measurement
technique that can be used in analytics. Although the main objective of this study is to …

Non-iterative and fast deep learning: Multilayer extreme learning machines

J Zhang, Y Li, W **ao, Z Zhang - Journal of the Franklin Institute, 2020‏ - Elsevier
In the past decade, deep learning techniques have powered many aspects of our daily life,
and drawn ever-increasing research interests. However, conventional deep learning …

Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research

S Lessmann, B Baesens, HV Seow… - European Journal of …, 2015‏ - Elsevier
Many years have passed since Baesens et al. published their benchmarking study of
classification algorithms in credit scoring [Baesens, B., Van Gestel, T., Viaene, S …

Predicting compressive strength of lightweight foamed concrete using extreme learning machine model

ZM Yaseen, RC Deo, A Hilal, AM Abd, LC Bueno… - … in Engineering Software, 2018‏ - Elsevier
In this research, a machine learning model namely extreme learning machine (ELM) is
proposed to predict the compressive strength of foamed concrete. The potential of the ELM …

Trends in extreme learning machines: A review

G Huang, GB Huang, S Song, K You - Neural Networks, 2015‏ - Elsevier
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 …

Extreme theory of functional connections: A fast physics-informed neural network method for solving ordinary and partial differential equations

E Schiassi, R Furfaro, C Leake, M De Florio… - Neurocomputing, 2021‏ - Elsevier
We present a novel, accurate, fast, and robust physics-informed neural network method for
solving problems involving differential equations (DEs), called Extreme Theory of Functional …