Statistical Uncertainty Estimation Using Random Forests and Its Application to Drought Forecast
Joint Authors
Chen, Junfei
Li, Ming
Wang, Weiguang
Source
Mathematical Problems in Engineering
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-09-24
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Drought is part of natural climate variability and ranks the first natural disaster in the world.
Drought forecasting plays an important role in mitigating impacts on agriculture and water resources.
In this study, a drought forecast model based on the random forest method is proposed to predict the time series of monthly standardized precipitation index (SPI).
We demonstrate model application by four stations in the Haihe river basin, China.
The random-forest- (RF-) based forecast model has consistently shown better predictive skills than the ARIMA model for both long and short drought forecasting.
The confidence intervals derived from the proposed model generally have good coverage, but still tend to be conservative to predict some extreme drought events.
American Psychological Association (APA)
Chen, Junfei& Li, Ming& Wang, Weiguang. 2012. Statistical Uncertainty Estimation Using Random Forests and Its Application to Drought Forecast. Mathematical Problems in Engineering،Vol. 2012, no. 2012, pp.1-12.
https://search.emarefa.net/detail/BIM-1029834
Modern Language Association (MLA)
Chen, Junfei…[et al.]. Statistical Uncertainty Estimation Using Random Forests and Its Application to Drought Forecast. Mathematical Problems in Engineering No. 2012 (2012), pp.1-12.
https://search.emarefa.net/detail/BIM-1029834
American Medical Association (AMA)
Chen, Junfei& Li, Ming& Wang, Weiguang. Statistical Uncertainty Estimation Using Random Forests and Its Application to Drought Forecast. Mathematical Problems in Engineering. 2012. Vol. 2012, no. 2012, pp.1-12.
https://search.emarefa.net/detail/BIM-1029834
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1029834