Abstract: Neural networks have been shown to be effective in modelling time series, with applications in the forecasting of electricity consumption. In applying neural networks to weekly electricity consumption data, several issues, such as selection of network architecture, network structure and input structure need to be addressed. This paper addresses these issues in relation to the current application and also demonstrates that considerable value is to be gained from incorporating the lessons learned from linear time series modelling into the current nonlinear analysis. Results for national Irish weekly electricity data demonstrate the potential improvements which can be obtained using the neural network approach
This paper deals with so-called feedforward neural network model which we consider from a statistica...
Power systems require the continuous balance of energy supply and demand for their appropriate funct...
This paper proposes a step-by-step technique for combining basic models that forecast electricity co...
Neural networks have been shown to be effective in modelling time series, with applications in the f...
This paper examines the application of artificial neural networks (ANNs) to the modelling and foreca...
This paper presents an artificial neural network (ANN) approach to electric energy consumption (EEC)...
Accurate electricity demand forecasts are critical for daily operations planning. They influence man...
Forecasting is an essential function in the electricity supply industry. Electricity demand forecast...
International audienceRecently, there has been a significant emphasis on the forecasting of the elec...
The recent decade has focused attention more than ever before on the increasing carbon emissions and...
The analysis of a time series is a problem well known to statisticians. Neural networks form the bas...
The tremendous rise of electrical energy demand worldwide has led to many problems related to effici...
In this study several Artificial Neural Network (ANN) models were experimented to predict electricit...
Accurate prediction of electricity demand can bring extensive benefits to any country as the forecas...
In this study several Artificial Neural Network (ANN) models were experimented to predict electricit...
This paper deals with so-called feedforward neural network model which we consider from a statistica...
Power systems require the continuous balance of energy supply and demand for their appropriate funct...
This paper proposes a step-by-step technique for combining basic models that forecast electricity co...
Neural networks have been shown to be effective in modelling time series, with applications in the f...
This paper examines the application of artificial neural networks (ANNs) to the modelling and foreca...
This paper presents an artificial neural network (ANN) approach to electric energy consumption (EEC)...
Accurate electricity demand forecasts are critical for daily operations planning. They influence man...
Forecasting is an essential function in the electricity supply industry. Electricity demand forecast...
International audienceRecently, there has been a significant emphasis on the forecasting of the elec...
The recent decade has focused attention more than ever before on the increasing carbon emissions and...
The analysis of a time series is a problem well known to statisticians. Neural networks form the bas...
The tremendous rise of electrical energy demand worldwide has led to many problems related to effici...
In this study several Artificial Neural Network (ANN) models were experimented to predict electricit...
Accurate prediction of electricity demand can bring extensive benefits to any country as the forecas...
In this study several Artificial Neural Network (ANN) models were experimented to predict electricit...
This paper deals with so-called feedforward neural network model which we consider from a statistica...
Power systems require the continuous balance of energy supply and demand for their appropriate funct...
This paper proposes a step-by-step technique for combining basic models that forecast electricity co...