This paper presents currently achieved results concerning methods of electrohydrodynamiceffect used in geophysics simulated with feedforward networks trained with backpropagation algorithm, radial basis function networks and generalized regression networks
The solution to a variety of engineering problems entails the simulation of a physical system. The m...
The inverse problems in electromagnetic system design, optimization, and identification received lat...
In this paper a neural network is used for the generation of a contour map of the ground conductivit...
This paper presents currently achieved results concerning methods of electrohydrodynamic effect used...
This paper presents an approach to model the nonlinear dynamic behaviors of the Automatic Depth Cont...
The applications of intelligent techniques have increased exponentially in recent days to study most...
AbstractThe applications of intelligent techniques have increased exponentially in recent days to st...
Abstract. The application of the generalised radial basis functions neural networks to the solution ...
Marine electromagnetic (EM) survey is an engineering endeavor to determine the location and dimens...
The automatic depth control electrohydraulic system of a certain minesweeping tank is complex nonlin...
In this work we investigate neural networks and subsequently physics-informed neural networks. Physi...
Trough is an interesting phenomenon in characterizing the behavior of the ionosphere, especially dur...
The Finite Element and Finite Difference methods are both widely used in estimating magnetic field ...
A backpropagation neural network was trained to estimate the spatial location (offset and depth) of ...
Multilayer neural networks, trained via the back-propagation rule, are proved to provide an efficien...
The solution to a variety of engineering problems entails the simulation of a physical system. The m...
The inverse problems in electromagnetic system design, optimization, and identification received lat...
In this paper a neural network is used for the generation of a contour map of the ground conductivit...
This paper presents currently achieved results concerning methods of electrohydrodynamic effect used...
This paper presents an approach to model the nonlinear dynamic behaviors of the Automatic Depth Cont...
The applications of intelligent techniques have increased exponentially in recent days to study most...
AbstractThe applications of intelligent techniques have increased exponentially in recent days to st...
Abstract. The application of the generalised radial basis functions neural networks to the solution ...
Marine electromagnetic (EM) survey is an engineering endeavor to determine the location and dimens...
The automatic depth control electrohydraulic system of a certain minesweeping tank is complex nonlin...
In this work we investigate neural networks and subsequently physics-informed neural networks. Physi...
Trough is an interesting phenomenon in characterizing the behavior of the ionosphere, especially dur...
The Finite Element and Finite Difference methods are both widely used in estimating magnetic field ...
A backpropagation neural network was trained to estimate the spatial location (offset and depth) of ...
Multilayer neural networks, trained via the back-propagation rule, are proved to provide an efficien...
The solution to a variety of engineering problems entails the simulation of a physical system. The m...
The inverse problems in electromagnetic system design, optimization, and identification received lat...
In this paper a neural network is used for the generation of a contour map of the ground conductivit...
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