Year of Graduation
Spaceship Temperature Modes Monitoring Based on Radial Basis Function Neural Network
The problem of determining spaceship’s thermal parameters at the end of the data transmission session based on current temperature mode and spaceship’s orientation was considered. The main goal of this paper is to explore the possibility of applying radial basis function neural network model to solve mentioned problem. There were implemented preprocessing techniques, neural network architecture was developed, an influence of built model’s parameters on learning process was analyzed, several learning algorithms were implemented in order to reduce the test error, testing was conducted and the results were analyzed.