Accurate prediction of ionospheric parameters is crucial for telecommunication companies. These parameters rely strongly on solar activity. In this paper, we analyze the use of neural networks for sunspot time series prediction. Three types of models are tested and experimental results are reported for a particular sunspot time series: the IR5 index
This thesis describes the search for a temporal model for predicting the peak ionospheric electron d...
The problem of forecasting hourly solar irradiance over a multi-step horizon is dealt with by using ...
The problem of forecasting hourly solar irradiance over a multi-step horizon is dealt with by using ...
Accurate prediction of ionospheric parameters is crucial for telecommunication companies. These para...
The ability to predict the future behavior of solar activity has become of extreme importance due to...
Researchers in many fields share a deep interest in the sunspot activity of the Sun. This kind of sol...
Studies of the Sun and the Earth’s atmosphere and climate consider solar variability as an important...
Studies of the Sun and the Earth’s atmosphere and climate consider solar variability as an important...
¾This paper presents a feedforward neural network approach to sunspot forecasting. The sunspot serie...
A recurrent connectionist network has been designed to model sunspot data. Preliminary experimental ...
A model was constructed to predict the amount of solar radiation that will make contact with the sur...
In this paper, multi step ahead prediction of monthly sunspot real time series are carried out. This...
The work of this thesis is concerned with investigating the application of artificial neural network...
The earliest systematic observance of sunspot activity is known to have been discovered by the Chine...
The present study describes a neural network approach for modeling and making short-term predictions...
This thesis describes the search for a temporal model for predicting the peak ionospheric electron d...
The problem of forecasting hourly solar irradiance over a multi-step horizon is dealt with by using ...
The problem of forecasting hourly solar irradiance over a multi-step horizon is dealt with by using ...
Accurate prediction of ionospheric parameters is crucial for telecommunication companies. These para...
The ability to predict the future behavior of solar activity has become of extreme importance due to...
Researchers in many fields share a deep interest in the sunspot activity of the Sun. This kind of sol...
Studies of the Sun and the Earth’s atmosphere and climate consider solar variability as an important...
Studies of the Sun and the Earth’s atmosphere and climate consider solar variability as an important...
¾This paper presents a feedforward neural network approach to sunspot forecasting. The sunspot serie...
A recurrent connectionist network has been designed to model sunspot data. Preliminary experimental ...
A model was constructed to predict the amount of solar radiation that will make contact with the sur...
In this paper, multi step ahead prediction of monthly sunspot real time series are carried out. This...
The work of this thesis is concerned with investigating the application of artificial neural network...
The earliest systematic observance of sunspot activity is known to have been discovered by the Chine...
The present study describes a neural network approach for modeling and making short-term predictions...
This thesis describes the search for a temporal model for predicting the peak ionospheric electron d...
The problem of forecasting hourly solar irradiance over a multi-step horizon is dealt with by using ...
The problem of forecasting hourly solar irradiance over a multi-step horizon is dealt with by using ...