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This paper presents a new approach for interpretation of residual gravity anomaly profiles, assuming horizontal cylinders as source. The new method, called Forced Neural Network (FNN), is introduced ...
In this work, Neural-Network-based single-station hourly daily foF2 and M(3000)F2 modelling of 15 European ionospheric stations is investigated. The data used are neural networks and hourly daily valu...
Local scaling and singularity properties of solar wind and geomagnetic time series were analysed using Hölder exponents . It was shown that in analysed cases due to the multifractality of fluctua...
This work is focused on the application of neural network based models to the analysis of total ozone (TO) time series. Processes that affect total ozone are extremely non linear, especially at the co...
In this work, an artificial neural network (ANN) model is developed and used to predict the presence of ducting phenomena for a specific time, taking into account ground values of atmospheric pressure...

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