Metaheuristic design of feedforward neural networks: A review of two decades of research
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 …
key interest among the researchers and practitioners of multiple disciplines. The FNN …
Artificial intelligence for control and optimization of boilers' performance and emissions: A review
Burning fossil fuels is a major concern for global warming control. In Saudi Arabia, steam
power plants that relay on boilers to produce the steam accounted for around 50% of the …
power plants that relay on boilers to produce the steam accounted for around 50% of the …
[PDF][PDF] Activation functions in neural networks
Artificial Neural Networks are inspired from the human brain and the network of neurons
present in the brain. The information is processed and passed on from one neuron to …
present in the brain. The information is processed and passed on from one neuron to …
Extreme learning machine: theory and applications
GB Huang, QY Zhu, CK Siew - Neurocomputing, 2006 - Elsevier
It is clear that the learning speed of feedforward neural networks is in general far slower than
required and it has been a major bottleneck in their applications for past decades. Two key …
required and it has been a major bottleneck in their applications for past decades. Two key …
Extreme learning machine: a new learning scheme of feedforward neural networks
GB Huang, QY Zhu, CK Siew - 2004 IEEE international joint …, 2004 - ieeexplore.ieee.org
It is clear that the learning speed of feedforward neural networks is in general far slower than
required and it has been a major bottleneck in their applications for past decades. Two key …
required and it has been a major bottleneck in their applications for past decades. Two key …
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 …
Universal approximation using incremental constructive feedforward networks with random hidden nodes
GB Huang, L Chen, CK Siew - IEEE transactions on neural …, 2006 - ieeexplore.ieee.org
According to conventional neural network theories, single-hidden-layer feedforward
networks (SLFNs) with additive or radial basis function (RBF) hidden nodes are universal …
networks (SLFNs) with additive or radial basis function (RBF) hidden nodes are universal …
A fast and accurate online sequential learning algorithm for feedforward networks
In this paper, we develop an online sequential learning algorithm for single hidden layer
feedforward networks (SLFNs) with additive or radial basis function (RBF) hidden nodes in a …
feedforward networks (SLFNs) with additive or radial basis function (RBF) hidden nodes in a …
Approximation theory of the MLP model in neural networks
A Pinkus - Acta numerica, 1999 - cambridge.org
In this survey we discuss various approximation-theoretic problems that arise in the
multilayer feedforward perceptron (MLP) model in neural networks. The MLP model is one of …
multilayer feedforward perceptron (MLP) model in neural networks. The MLP model is one of …
Comparison of convolutional neural networks for landslide susceptibility map** in Yanshan County, China
Assessments of landslide disasters are becoming increasingly urgent. The aim of this study
is to investigate a convolutional neural network (CNN) framework for landslide susceptibility …
is to investigate a convolutional neural network (CNN) framework for landslide susceptibility …