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.

References

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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