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.
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Bukhtoyarov, V., Semenkin, E., Shabalov, A. (2012). Neural Networks Ensembles Approach for Simulation of Solar Arrays Degradation Process. In: Corchado, E., Snášel, V., Abraham, A., Woźniak, M., Graña, M., Cho, SB. (eds) Hybrid Artificial Intelligent Systems. HAIS 2012. Lecture Notes in Computer Science(), vol 7208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28942-2_17
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DOI: https://doi.org/10.1007/978-3-642-28942-2_17
Publisher Name: Springer, Berlin, Heidelberg
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