This study presents comparative results obtained from employing four different neuro-fuzzy models to predict geomagnetic storms. Two of these neuro-fuzzy models can be classified as Brain Emotional Learning Inspired Models (BELIMs). These two models are BELFIS (Brain Emotional Learning Based Fuzzy Inference System) and BELRFS (Brain Emotional Learning Recurrent Fuzzy System). The two other models are Adaptive Neuro-Fuzzy Inference System (ANFIS) and Locally Linear Model Tree (LoLiMoT) learning algorithm, two powerful neuro-fuzzy models to accurately predict a nonlinear system. These models are compared for their ability to predict geomagnetic storms using the AE index
This thesis shows how artificial neural networks (ANNs) can be applied to predict geomagnetic activi...
Accurate prediction of total electron content (TEC) is important for monitoring the behavior of the ...
The prediction of solar radiation is very important tool in climatology, hydrology and energy applic...
In this paper an architecture based on the anatomical structure of the emotional network in the brai...
This paper briefly describes how the neural structure of fear conditioning has inspired to develop a...
Accurate prediction of solar activity as one aspect of space weather phenomena is essential to decre...
In this thesis the mammalian nervous system and mammalian brain have been used as inspiration to dev...
© 2019 IEEE. The paper proposes a prediction model of dynamics of time series of magnetic storms num...
© 2019 IEEE. The paper proposes a prediction model of dynamics of time series of magnetic storms num...
This paper discusses the estimation of zonal geomagnetic indices of two super geomagnetic activities...
Prior to an earthquake, there is energy storage in the seismogenic area, the release of which result...
An artificial feed-forward neural network with one hidden layer and error back-propagation learning ...
The study demonstrated the technology for searching nonlinear correlations between the intensity ind...
An artificial feed-forward neural network with one hidden layer and error back-propagation learning...
Summarization: During the last decades, floods are getting more and more dangerous and they cause a ...
This thesis shows how artificial neural networks (ANNs) can be applied to predict geomagnetic activi...
Accurate prediction of total electron content (TEC) is important for monitoring the behavior of the ...
The prediction of solar radiation is very important tool in climatology, hydrology and energy applic...
In this paper an architecture based on the anatomical structure of the emotional network in the brai...
This paper briefly describes how the neural structure of fear conditioning has inspired to develop a...
Accurate prediction of solar activity as one aspect of space weather phenomena is essential to decre...
In this thesis the mammalian nervous system and mammalian brain have been used as inspiration to dev...
© 2019 IEEE. The paper proposes a prediction model of dynamics of time series of magnetic storms num...
© 2019 IEEE. The paper proposes a prediction model of dynamics of time series of magnetic storms num...
This paper discusses the estimation of zonal geomagnetic indices of two super geomagnetic activities...
Prior to an earthquake, there is energy storage in the seismogenic area, the release of which result...
An artificial feed-forward neural network with one hidden layer and error back-propagation learning ...
The study demonstrated the technology for searching nonlinear correlations between the intensity ind...
An artificial feed-forward neural network with one hidden layer and error back-propagation learning...
Summarization: During the last decades, floods are getting more and more dangerous and they cause a ...
This thesis shows how artificial neural networks (ANNs) can be applied to predict geomagnetic activi...
Accurate prediction of total electron content (TEC) is important for monitoring the behavior of the ...
The prediction of solar radiation is very important tool in climatology, hydrology and energy applic...