Angelo Scacciavillani
Neural network data analysis for virtual air data sensors.
Rel. Piero Gili, Alberto Brandl. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Aerospaziale, 2018
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Abstract
Over the years it is getting more present the use of machine learning techniques applied to many different disciplines. In aeronautic field they are used as a substitute or as an enrichment of flight systems in order to have a better production of flight data. The main three aspects studied in neural networks, which are one of the many machine learning techniques and the one used in this thesis, are the network architecture, the training phase and the testing phase.There are other very important aspects such as the various methods for carrying out these operations. The knowledge of the latter is very important in order to obtain very precise networks in the purpose that is set.
This thesis is in fact aimed at finding a method for the improvement of one of these aspects
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