Applicability of neural nets in time series forecasting has been considered and researched. For this, training of neural network on various time series with preliminary selection of optimal hyperparameters has been performed. Comparative analysis of received neural networking forecasting model with linear regression has been performed. Conditions, affecting on accuracy and stability of results of the neural network, have been revealed
This paper reports about a comparative study on several linear and nonlinear feedforward and recurre...
Neural Network approaches to time series prediction are briefly discussed, and the need to find the ...
In this paper, the task of assessment of numerical conditioning of multilayer perceptron, forecastin...
FFNN Feed Forward Neural Nets are one of the most widely used neural nets. In this thesis the FFNN a...
summary:Artificial neural networks (ANN) have received a great deal of attention in many fields of e...
The analysis of a time series is a problem well known to statisticians. Neural networks form the bas...
Abstract: The following paper tries to develop a simple neural network approach to analyse time seri...
The problem of forecasting a time series with a neural network is well-defined when considering a si...
In recent years, artificial neural networks have being successfully used in time series analysis. Us...
It is important to predict a time series because many problems that are related to prediction such a...
The development of machine learning research has provided statistical innovations and further develo...
Thesis (M.Sc. (Computer Science))--North-West University, Vaal Triangle Campus, 2010.Time series for...
This study offers a description and comparison of the main models of Artificial Neural Networks (ANN...
AbstractThe objective of this paper is to compare time series forecasting by using three different b...
This study shows that neural networks have been advocated as an alternative to traditional statistic...
This paper reports about a comparative study on several linear and nonlinear feedforward and recurre...
Neural Network approaches to time series prediction are briefly discussed, and the need to find the ...
In this paper, the task of assessment of numerical conditioning of multilayer perceptron, forecastin...
FFNN Feed Forward Neural Nets are one of the most widely used neural nets. In this thesis the FFNN a...
summary:Artificial neural networks (ANN) have received a great deal of attention in many fields of e...
The analysis of a time series is a problem well known to statisticians. Neural networks form the bas...
Abstract: The following paper tries to develop a simple neural network approach to analyse time seri...
The problem of forecasting a time series with a neural network is well-defined when considering a si...
In recent years, artificial neural networks have being successfully used in time series analysis. Us...
It is important to predict a time series because many problems that are related to prediction such a...
The development of machine learning research has provided statistical innovations and further develo...
Thesis (M.Sc. (Computer Science))--North-West University, Vaal Triangle Campus, 2010.Time series for...
This study offers a description and comparison of the main models of Artificial Neural Networks (ANN...
AbstractThe objective of this paper is to compare time series forecasting by using three different b...
This study shows that neural networks have been advocated as an alternative to traditional statistic...
This paper reports about a comparative study on several linear and nonlinear feedforward and recurre...
Neural Network approaches to time series prediction are briefly discussed, and the need to find the ...
In this paper, the task of assessment of numerical conditioning of multilayer perceptron, forecastin...