Open AccessDesign of an Error Estimation Algorithm for Time Series Data Prediction in Attitude Controlled Systems
Author(s) -
M. Raja,
Kokila VASUDEVAN,
Kartikay Singh,
Aishwerya Singh,
Ayush Gupta
Publication year - 2021
Publication title -
incas buletin
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.282
H-Index - 10
eISSN - 2247-4528
pISSN - 2066-8201
DOI - 10.13111/2066-8201.2021.13.3.12
Subject(s) - computer science , algorithm , stability (learning theory) , series (stratigraphy) , time series , regression , linear regression , mean squared prediction error , regression analysis , value (mathematics) , data mining , mathematics , statistics , machine learning , paleontology , biology
This research presents an error estimation approach with the combination of traditional multilevel techniques used to minimize errors for an accurate prediction and to investigate the behavior of such an algorithm for a satellite. The traditional techniques mentioned above are a combination derived from multiple regression techniques and perform a case study for data analysis. A linear plot can easily be predicted, however if a system tends to deviate toward non-linearity the overall result derived from such an algorithm can be non-reliable since each value would depict a completely different output at different levels. The stability of the fixed regression derived is used to determine the accuracy of the system.