Annual Runoff Prediction Based on Least Square Support Vector Machines-Markov Chain Combined Model

Xiu Ping Zhou; Cong Zhu; Tian Xiang Li

doi:10.4028/www.scientific.net/AMR.418-420.2114

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 418-420Annual Runoff Prediction Based on Least Square...

Annual Runoff Prediction Based on Least Square Support Vector Machines-Markov Chain Combined Model

Abstract:

A new annual runoff prediction model was proposed by combining the least squares support vector machines and markov chains named LSSVM-MC. Firstly, adopt the least squares support vector machines to predict annual runoff as the first step prediction. Then regarding the series of prediction errors as a process of Markov chain, adopt Markov chain method to predict the potential error as the second step prediction. At last, subtract the two-step prediction results to get the final prediction value. The case study shows that the combined model effectively improves the annual runoff prediction accuracy.

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Materials Processing Technology, ICAMMP2011

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Periodical:

Advanced Materials Research (Volumes 418-420)

Pages:

2114-2117

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.418-420.2114

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Online since:

December 2011

Authors:

Xiu Ping Zhou, Cong Zhu, Tian Xiang Li

Keywords:

Annual Runoff Prediction, Combined Model, LSSVM, Markov Chain

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