In this article, atmospheric parameters are modelled by using artificial neural networks and the obtained models are compared with atmospheric lookup tables in terms of accuracy, speedup and memory usage. First, input and output data were generated for the five different atmosphere layers divided by altitude ranges using the U.S. Standard Atmosphere 1976 atmosphere model. Then, the artificial neural networks trained with these data were added to the simulation and measurements were taken. The results show that the use of artificial neural network modelled by using atmospheric data instead of atmospheric lookup table is more efficient and encourages new studies.


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    Title :

    Modelling of Atmospheric Parameters Using Artificial Neural Networks


    Contributors:


    Publication date :

    2019-06-01


    Size :

    9889222 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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