Open AccessSpace Detector Health Prediction Based on Online Neural Network
Author(s) -
Ying Zhang,
Feng Tian,
Wei Chen,
Ran Li
Publication year - 2022
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 - 10.1088/1742-6596/2242/1/012042
Subject(s) - detector , artificial neural network , computer science , set (abstract data type) , space (punctuation) , data set , artificial intelligence , scheme (mathematics) , data mining , training set , algorithm , machine learning , real time computing , telecommunications , mathematics , mathematical analysis , programming language , operating system
The paper presents a real - time online neural network algorithm for space detector health prediction. This method is suitable for embedded space detector, avoiding the disposal scheme that can not be processed online and can only be remedied afterwards, and adopting embedded real-time neural network model with preserved performance after compression. It consists of five parts: data input simulation, data set training model, prediction model, combination model and health degree calculation.