Spacecraft Solar Arrays Degradation Forecasting with Evolutionary Designed ANN-based Predictors

Maria Semenkina, Shakhnaz Akhmedova, Eugene Semenkin, Ivan Ryzhikov

2014

Abstract

The problem of forecasting the degradation of spacecraft solar arrays is considered. The application of ANN-based predictors is proposed and their automated design with self-adaptive evolutionary and bio-inspired algorithms is suggested. The adaptation of evolutionary algorithms is implemented on the base of the algorithms’ self-configuration. The island model for the bio-inspired algorithms cooperation is used. The performance of four developed algorithms for automated design of ANN-based predictors is estimated on real-world data and the most perspective approach is determined.

Paper Citation

in Harvard Style

Semenkina M., Akhmedova S., Semenkin E. and Ryzhikov I. (2014). Spacecraft Solar Arrays Degradation Forecasting with Evolutionary Designed ANN-based Predictors . In Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-039-0, pages 421-428. DOI: 10.5220/0005122004210428

in Bibtex Style

@conference{icinco14,
author={Maria Semenkina and Shakhnaz Akhmedova and Eugene Semenkin and Ivan Ryzhikov},
title={Spacecraft Solar Arrays Degradation Forecasting with Evolutionary Designed ANN-based Predictors},
booktitle={Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2014},
pages={421-428},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005122004210428},
isbn={978-989-758-039-0},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Spacecraft Solar Arrays Degradation Forecasting with Evolutionary Designed ANN-based Predictors
SN - 978-989-758-039-0
AU - Semenkina M.
AU - Akhmedova S.
AU - Semenkin E.
AU - Ryzhikov I.
PY - 2014
SP - 421
EP - 428
DO - 10.5220/0005122004210428