Design of Deep Belief Networks for Short-Term Prediction of Drought Index Using Data in the Huaihe River Basin
Joint Authors
Chen, Junfei
Jin, Qiongji
Chao, Jing
Source
Mathematical Problems in Engineering
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-05-08
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
With the global climate change, drought disasters occur frequently.
Drought prediction is an important content for drought disaster management, planning and management of water resource systems of a river basin.
In this study, a short-term drought prediction model based on deep belief networks (DBNs) is proposed to predict the time series of different time-scale standardized precipitation index (SPI).
The DBN model is applied to predict the drought time series in the Huaihe River Basin, China.
Compared with BP neural network, the DBN-based drought prediction model has shown better predictive skills than the BP neural network for the different time-scale SPI.
This research can improve drought prediction technology and be helpful for water resources managers and decision makers in managing drought disasters.
American Psychological Association (APA)
Chen, Junfei& Jin, Qiongji& Chao, Jing. 2012. Design of Deep Belief Networks for Short-Term Prediction of Drought Index Using Data in the Huaihe River Basin. Mathematical Problems in Engineering،Vol. 2012, no. 2012, pp.1-16.
https://search.emarefa.net/detail/BIM-1001421
Modern Language Association (MLA)
Chen, Junfei…[et al.]. Design of Deep Belief Networks for Short-Term Prediction of Drought Index Using Data in the Huaihe River Basin. Mathematical Problems in Engineering No. 2012 (2012), pp.1-16.
https://search.emarefa.net/detail/BIM-1001421
American Medical Association (AMA)
Chen, Junfei& Jin, Qiongji& Chao, Jing. Design of Deep Belief Networks for Short-Term Prediction of Drought Index Using Data in the Huaihe River Basin. Mathematical Problems in Engineering. 2012. Vol. 2012, no. 2012, pp.1-16.
https://search.emarefa.net/detail/BIM-1001421
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1001421