Abstract
This paper presents a parallel-structure fuzzy system (PSFS) for prediction of sunspot cycle in the railway communication and power systems based on smoothed sunspot number time series. The PSFS consists of a multiple number of fuzzy systems connected in parallel. Each component fuzzy system in the PSFS predicts the same future data independently based on its past time series data with different embedding dimension and time delay. According to the embedding dimension and the time delay, the component fuzzy system takes various input-output pairs. The PSFS determines the final predicted value as an average of all the outputs of the component fuzzy systems excluding the predicted data with the minimum and the maximum values in order to reduce error accumulation effect.
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Kim, MS. (2006). Parallel-Structure Fuzzy System for Sunspot Cycle Prediction in the Railway Systems. In: Wang, L., Jiao, L., Shi, G., Li, X., Liu, J. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2006. Lecture Notes in Computer Science(), vol 4223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881599_114
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DOI: https://doi.org/10.1007/11881599_114
Publisher Name: Springer, Berlin, Heidelberg
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