Weighs and bias data for the artificial neural network models, and fluent deployable codes for implementing these modelsTHIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV
Three neural network models were used for prediction of adsorption equilibria of binary vapour mixtu...
In studies of the interstellar medium in galaxies, radiative transfer models of molecular emission a...
The concept of neural network models (NNM) is a statistical strategy which can be used if a superpos...
Weighs and bias data for the artificial neural network models, and fluent deployable codes for imple...
Synthetic spectra calculated from model solar atmospheres are central to our understanding of the co...
© 2019 IOP Publishing Ltd. All rights reserved. An artificial neural multi-layer network has been de...
The radiative transfer equations are well known, but radiation parametrizations in atmospheric model...
Context. Computing spectra from 3D simulations of stellar atmospheres when allowing for departures f...
We propose a novel machine learning algorithm for simulating radiative transfer. Our algorithm is ba...
The paper deals with the development of methods for solving the inverse problem of gaseous media opt...
The problem of application of artificial neural networks for approximation of inverse models of temp...
Abstract. Nitric acid production plants emit small amounts of nitrogen oxides (NOx) to the environme...
To retrieve aerosol properties from satellite measurements of the oxygen A-band in the near-infrared...
Infrared remote sensing is an extended technique to measure ”in situ” atmospheric pollutant gas conc...
For the majority of the particles in the atmosphere, calculations of scattering energy loss are incr...
Three neural network models were used for prediction of adsorption equilibria of binary vapour mixtu...
In studies of the interstellar medium in galaxies, radiative transfer models of molecular emission a...
The concept of neural network models (NNM) is a statistical strategy which can be used if a superpos...
Weighs and bias data for the artificial neural network models, and fluent deployable codes for imple...
Synthetic spectra calculated from model solar atmospheres are central to our understanding of the co...
© 2019 IOP Publishing Ltd. All rights reserved. An artificial neural multi-layer network has been de...
The radiative transfer equations are well known, but radiation parametrizations in atmospheric model...
Context. Computing spectra from 3D simulations of stellar atmospheres when allowing for departures f...
We propose a novel machine learning algorithm for simulating radiative transfer. Our algorithm is ba...
The paper deals with the development of methods for solving the inverse problem of gaseous media opt...
The problem of application of artificial neural networks for approximation of inverse models of temp...
Abstract. Nitric acid production plants emit small amounts of nitrogen oxides (NOx) to the environme...
To retrieve aerosol properties from satellite measurements of the oxygen A-band in the near-infrared...
Infrared remote sensing is an extended technique to measure ”in situ” atmospheric pollutant gas conc...
For the majority of the particles in the atmosphere, calculations of scattering energy loss are incr...
Three neural network models were used for prediction of adsorption equilibria of binary vapour mixtu...
In studies of the interstellar medium in galaxies, radiative transfer models of molecular emission a...
The concept of neural network models (NNM) is a statistical strategy which can be used if a superpos...