The results of prediction of geomagnetic indexes characterizing the state of the Earth's magnetosphere obtained with the help of artificial neural networks (ANN) for various prediction horizons are presented. The forecasts are based on multivariate time series including the values of the geomagnetic indices themselves, as well as data about the parameters of solar wind and interplanetary magnetic field, during several latest hours
The paper presents our software system for estimation the degree of disturbance of the geomagnetic f...
Artificial Neural Network (ANN) has proven to be very successful in forecasting a variety of irregul...
Artificial Neural Network (ANN) has proven to be very successful in forecasting a variety of irregul...
This thesis shows how artificial neural networks (ANNs) can be applied to predict geomagnetic activi...
In this thesis, we present models which belongs to the field of artificial intelligence to predict t...
This paper discusses the estimation of zonal geomagnetic indices of two super geomagnetic activities...
This thesis concerns the application of artificial neural network techniques to space weather physic...
An artificial feed-forward neural network with one hidden layer and error back-propagation learning ...
This paper describes a method to obtain local magnetic index, K, from the global index, Kp. Until no...
© 2019 IEEE. The paper presents a method for estimating geomagnetic and solar activity indices using...
study their time evolution in years. In order to find the best NN for the time predictions, we teste...
© 2019 IEEE. The paper presents a method for estimating geomagnetic and solar activity indices using...
<p>This paper describes a method to obtain local magnetic index, K, from the global index, Kp. Until...
The paper presents our software system for estimation the degree of disturbance of the geomagnetic f...
An artificial feed-forward neural network with one hidden layer and error back-propagation learning...
The paper presents our software system for estimation the degree of disturbance of the geomagnetic f...
Artificial Neural Network (ANN) has proven to be very successful in forecasting a variety of irregul...
Artificial Neural Network (ANN) has proven to be very successful in forecasting a variety of irregul...
This thesis shows how artificial neural networks (ANNs) can be applied to predict geomagnetic activi...
In this thesis, we present models which belongs to the field of artificial intelligence to predict t...
This paper discusses the estimation of zonal geomagnetic indices of two super geomagnetic activities...
This thesis concerns the application of artificial neural network techniques to space weather physic...
An artificial feed-forward neural network with one hidden layer and error back-propagation learning ...
This paper describes a method to obtain local magnetic index, K, from the global index, Kp. Until no...
© 2019 IEEE. The paper presents a method for estimating geomagnetic and solar activity indices using...
study their time evolution in years. In order to find the best NN for the time predictions, we teste...
© 2019 IEEE. The paper presents a method for estimating geomagnetic and solar activity indices using...
<p>This paper describes a method to obtain local magnetic index, K, from the global index, Kp. Until...
The paper presents our software system for estimation the degree of disturbance of the geomagnetic f...
An artificial feed-forward neural network with one hidden layer and error back-propagation learning...
The paper presents our software system for estimation the degree of disturbance of the geomagnetic f...
Artificial Neural Network (ANN) has proven to be very successful in forecasting a variety of irregul...
Artificial Neural Network (ANN) has proven to be very successful in forecasting a variety of irregul...