Open AccessBP Neural Network for Temperature Prediction of Alpha Magnetic Spectrometer on Orbit
Author(s) -
Fei Yang,
Qiang Sun,
Lin Cheng
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1824/1/012004
Subject(s) - artificial neural network , mean squared error , spectrometer , orbit (dynamics) , alpha (finance) , algorithm , computer science , thermal , artificial intelligence , mathematics , physics , meteorology , statistics , engineering , aerospace engineering , optics , construct validity , psychometrics
A BP neural network combined with the Adam optimization algorithm and the Mini-batches Learning algorithm was established for predicting the temperature of BOX-C on Alpha Magnetic Spectrometer (AMS) in this paper. After training, the Mean Squared Error (MSE) of the prediction results under the normal operating condition is 0.14 and this shows that the model can be used to predict the temperature of BOX-C with a satisfying accuracy. The model paves the ground for AMS thermal control on orbit.