NDLI: Application of Relevance Vector Machine to Downscale GCMs to Runoff in Hydrology

Content Provider	IEEE Xplore Digital Library
Author	Hua Chen Wei Xiong Jing Guo
Copyright Year	2008
Description	Author affiliation: State Key Lab. of Water Resources & Hydropower Eng. Sci., Wuhan Univ., Wuhan (Hua Chen; Jing Guo)
Abstract	As relevance vector machine (RVM) can powerfully manage complexity to regression and classification basing on the concept of probabilistic Bayesian learning framework, it has been widely used in dealing with various recognition problems. In present study we applied RVM as a statistical downscaling method to climate change impact on hydrology and water resources. General circulation models (GCMs) are main tools for study global climate change, however, their simulate results cannot be used directly to evaluate the impact of climate change on hydrology in basin scale for their large and coarse scale. By applying downscaling approach based on RVM, the complex non-linear relationship between the climate factors of GCMs and runoff in basin scale was bridged. The impact of climate change on runoff was assessed by using the established relationship. Comparing with the other two downscaling approach, least support vector machine (LSSVM) and Back propagation neural network (BPNN), the results showed that RVM is suitable for assessing climate change impact on hydrology as rational modeling accuracy and fast modeling speed.
Starting Page	598
Ending Page	601
File Size	247582
Page Count	4
File Format	PDF
ISBN	9780769533056
DOI	10.1109/FSKD.2008.669
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-18
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Knowledge engineering statistical downscaling Hydroelectric power generation RVM Support vector machines Hydrology BPNN Bayesian methods Neural networks Support vector machine classification LSSVM Large-scale systems Water resources Power engineering and energy climate change
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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