Proceedings of the 2016 5th International Conference on Sustainable Energy and Environment Engineering (ICSEEE 2016)

A Novel Prediction Approach for Runoff Based On Hybrid HMM-SVM Model

Authors
Feng Chen, Yongqing Su, Yin Wang
Corresponding Author
Feng Chen
Available Online December 2016.
DOI
https://doi.org/10.2991/icseee-16.2016.23How to use a DOI?
Keywords
Hidden Markov Model, Shape Based Clustering, SVM, Runoff Prediction
Abstract

This research demonstrates an application of Hidden Markov Model (HMM) and Support Vector Machine (SVM) for watershed-runoff forecasts. HMM is used for shape-based clustering by calculating log-likelihood values of each data to identify data in the data set with similar data pattern.Then we put these data into different classes based on their shapes and train their corresponding SVM model to predict the output of the system finally. The applications of daily runoff and monthly runoff are used for testing the competence of this method and experimental results demonstrate that this hybrid HMM-SVM algorithm can meet the prediction requirement and has high prediction accuracy.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

Volume Title
Proceedings of the 2016 5th International Conference on Sustainable Energy and Environment Engineering (ICSEEE 2016)
Series
Advances in Engineering Research
Publication Date
December 2016
ISBN
978-94-6252-278-7
ISSN
2352-5401
DOI
https://doi.org/10.2991/icseee-16.2016.23How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Feng Chen
AU  - Yongqing Su
AU  - Yin Wang
PY  - 2016/12
DA  - 2016/12
TI  - A Novel Prediction Approach for Runoff Based On Hybrid HMM-SVM Model
BT  - Proceedings of the 2016 5th International Conference on Sustainable Energy and Environment Engineering (ICSEEE 2016)
PB  - Atlantis Press
SP  - 135
EP  - 139
SN  - 2352-5401
UR  - https://doi.org/10.2991/icseee-16.2016.23
DO  - https://doi.org/10.2991/icseee-16.2016.23
ID  - Chen2016/12
ER  -