Review on methods to fix number of hidden neurons in neural networks
This paper reviews methods to fix a number of hidden neurons in neural networks for the
past 20 years. And it also proposes a new method to fix the hidden neurons in Elman …
past 20 years. And it also proposes a new method to fix the hidden neurons in Elman …
Intrusion detection for IoT based on improved genetic algorithm and deep belief network
With the advent of the Internet of Things (IoT), the security of the network layer in the IoT is
getting more and more attention. The traditional intrusion detection technologies cannot be …
getting more and more attention. The traditional intrusion detection technologies cannot be …
Application of neural network in prediction of temperature: a review
C Johnstone, ED Sulungu - Neural computing and applications, 2021 - Springer
The aim of this study was to review different literatures to assess the applicability of artificial
neural network in predicting temperature. Temperature prediction as part of weather …
neural network in predicting temperature. Temperature prediction as part of weather …
Synergy of ICESat-2 and Landsat for mapping forest aboveground biomass with deep learning
Spatially continuous estimates of forest aboveground biomass (AGB) are essential to
supporting the sustainable management of forest ecosystems and providing invaluable …
supporting the sustainable management of forest ecosystems and providing invaluable …
Comparative analysis on hidden neurons estimation in multi layer perceptron neural networks for wind speed forecasting
M Madhiarasan, SN Deepa - Artificial Intelligence Review, 2017 - Springer
In this paper methodologies are proposed to estimate the number of hidden neurons that are
to be placed numbers in the hidden layer of artificial neural networks (ANN) and certain new …
to be placed numbers in the hidden layer of artificial neural networks (ANN) and certain new …
[HTML][HTML] Prediction of the metallurgical performances of a batch flotation system by image analysis and neural networks
It is now generally accepted that froth appearance is a good indicative of the flotation
performance. In this paper, the relationship between the process conditions and the froth …
performance. In this paper, the relationship between the process conditions and the froth …
Geometrical interpretation and design of multilayer perceptrons
The multilayer perceptron (MLP) neural network is interpreted from the geometrical
viewpoint in this work, that is, an MLP partition an input feature space into multiple …
viewpoint in this work, that is, an MLP partition an input feature space into multiple …
A quantitative evaluation of global, rule-based explanations of post-hoc, model agnostic methods
Understanding the inferences of data-driven, machine-learned models can be seen as a
process that discloses the relationships between their input and output. These relationships …
process that discloses the relationships between their input and output. These relationships …
A novel criterion to select hidden neuron numbers in improved back propagation networks for wind speed forecasting
M Madhiarasan, SN Deepa - Applied intelligence, 2016 - Springer
This paper analyzes various earlier approaches for selection of hidden neuron numbers in
artificial neural networks and proposes a novel criterion to select the hidden neuron …
artificial neural networks and proposes a novel criterion to select the hidden neuron …
Prediction of building's thermal performance using LSTM and MLP neural networks
M Martínez Comesaña, L Febrero-Garrido… - Applied Sciences, 2020 - mdpi.com
Accurate prediction of building indoor temperatures and thermal demand is of great help to
control and optimize the energy performance of a building. However, building thermal inertia …
control and optimize the energy performance of a building. However, building thermal inertia …