Neural networks ensembles approach for simulation of solar arrays degradation process

Authors:
Vladimir Bukhtoyarov;Eugene Semenkin;Andrey Shabalov
Affiliations:
Information Seurity Department, Siberian State Aerospace University, Krasnoyarsk, Russia;Department of System Analysis and Operations Research, Siberian State Aerospace University, Krasnoyarsk, Russia;Department of System Analysis and Operations Research, Siberian State Aerospace University, Krasnoyarsk, Russia
Venue:
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part I
Year:
2012

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Abstract

Neural networks ensembles are powerful tools for solving modeling and time series forecasting problems. This approach is based on cooperative usage of neural networks for problem solving. The two major stages of the neural networks ensemble construction are: design and training of the component networks and combining of the component networks predictions to produce the ensemble output. In this paper developed evolutionary approach for neural networks ensembles automatic design is reviewed briefly. This approach is based on the operators of the well-known evolutionary algorithms and requires fewer parameters to be tuned providing more flexible and adaptive solutions. Results of the neural networks ensemble approach applying for modeling of spacecrafts arrays degradation are discussed.