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- W2924783797 abstract "This paper presents a study into the utilization of the non-parametric statistic combined with the Bayesian paradigm for solar irradiance conditions clustering. A Dirichlet-multinomial mixture model is applied to automatically adapt to the correct complexity level and size of the model, and therefore, fit complex probability functions. Posterior computation relies on a numerical procedure based on Markov Chain Monte-Carlo algorithm. Experiments were conducted using three years of solar irradiance data carried out in Rabat, capital of Morocco (34°N latitude, 6°50'W longitude) with a sampling-rate of 6-min. The authors of this work are big supporters of open-source codes, therefore, all methods presented in this manuscript is openly available as a downloadable R-package from https://github.com/frimane/SolMultinomClass." @default.
- W2924783797 created "2019-04-01" @default.
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- W2924783797 date "2019-03-28" @default.
- W2924783797 modified "2023-09-26" @default.
- W2924783797 title "Automatic classification of daily-histograms of solar irradiance in Morocco" @default.
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- W2924783797 doi "https://doi.org/10.1145/3314074.3314098" @default.
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