期刊
INTERNATIONAL JOURNAL OF BIOMETEOROLOGY
卷 61, 期 4, 页码 647-656出版社
SPRINGER
DOI: 10.1007/s00484-016-1242-8
关键词
Poaceae; Pollen; Random forest; Forecasting; Time series
资金
- Ministerio de Economia y Competitividad, Gobierno de Espana, through a Ramon y Cajal grant [RYC-2012-11984]
In this paper, we approach the problem of predicting the concentrations of Poaceae pollen which define the main pollination season in the city of Madrid. A classification-based approach, based on a computational intelligence model (random forests), is applied to forecast the dates in which risk concentration levels are to be observed. Unlike previous works, the proposal extends the range of forecasting horizons up to 6 months ahead. Furthermore, the proposed model allows to determine the most influential factors for each horizon, making no assumptions about the significance of the weather features. The performace of the proposed model proves it as a successful tool for allergy patients in preventing and minimizing the exposure to risky pollen concentrations and for researchers to gain a deeper insight on the factors driving the pollination season.
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