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Knowledge and Information Systems
Erschienen in: Knowledge and Information Systems 1/2017

21.11.2016 | Regular Paper

Wind speed parameters sensitivity analysis based on fractals and neuro-fuzzy selection technique

verfasst von: Vlastimir Nikolić, Vojislav V. Mitić, Ljubiša Kocić, Dalibor Petković

Erschienen in: Knowledge and Information Systems | Ausgabe 1/2017

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Abstract

Fluctuation of wind speed affects wind energy systems since the potential wind power is proportional the cube of wind speed. Hence precise prediction of wind speed is very important to improve the performances of the systems. Due to unstable behavior of the wind speed above different terrains, in this study fractal characteristics of the wind speed series were analyzed. According to the self-similarity characteristic and the scale invariance, the fractal extrapolate interpolation prediction can be performed by extending the fractal characteristic from internal interval to external interval. Afterward neuro-fuzzy technique was applied to the fractal data because of high nonlinearity of the data. The neuro-fuzzy approach was used to detect the most important variables which affect the wind speed according to the fractal dimensions. The main goal was to investigate the influence of terrain roughness length and different heights of the wind speed on the wind speed prediction.
Vorheriger Artikel Exploiting interactions of review text, hidden user communities and item groups, and time for collaborative filtering
Nächster Artikel Random indexing of multidimensional data

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Metadaten
Titel
Wind speed parameters sensitivity analysis based on fractals and neuro-fuzzy selection technique
verfasst von
Vlastimir Nikolić
Vojislav V. Mitić
Ljubiša Kocić
Dalibor Petković
Publikationsdatum
21.11.2016
Verlag
Springer London
Erschienen in
Knowledge and Information Systems / Ausgabe 1/2017
Print ISSN: 0219-1377
Elektronische ISSN: 0219-3116
DOI
https://doi.org/10.1007/s10115-016-1006-0

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