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 …

Neural networks with a good modeling capability have been used increasingly to predict
and forecast solar radiation. Even diverse application of neural network has been reported …

Digital financial assets such as cryptocurrency are playing an increasingly crucial role in the
digital economy era. Cryptocurrency is characterized by significant volatility and asset price …

A constrained optimization method based on back-propagation (BP) neural network is
proposed in this paper. Taking the maximization of output for example, using unipolar …

Incomparable properties of high-temperature-resistant alloys demand the hunt for front-line
skills to machining these materials. Usage of conventional cooling mode at elevated …

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 …

The prediction accuracy of concrete compressive strength is important and considered a
challenging task, aiming at reducing costly and time‐consuming experiments. Moreover …

There is a large amount of useful information from past experimental tests, which are usually
ignored in test-setup for the new ones. Variation of assumptions, materials, test procedures …

Nowadays, special concrete-like self-compacting concrete (SCC) requires sustainability by
introducing recycled aggregates as a partial replacement for natural aggregate …

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 …