Wind Speed Forecast Based on Support Vector Machine

DOI

10.2991/iccahe-16.2016.9How to use a DOI?

Keywords

support vector regression; wind speed; forecast

Abstract

Environmental pollution, climate change, energy tension is now the global prominent question, the development and utilization of renewable energy to become one of the key measures to solve these problems. Wind power acts as a kind of safety, environmental protection, clean, abundant renewable energy by all countries focusing on and extensive using. The uncertainty of wind power makes high demands for operation scheduling, and more accurate wind speed forecast is of great significance to the effective use of wind power. Predictions based on support vector regression machine of wind speed were new application in recent years, it has received the widespread attentions. Using support vector regression machine predict the wind speed of a wind farm data, the analysis results show that the method of support vector regression machine can more accurately predict the wind speed and also proves the superiority of the prediction of wind speed.

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/).

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TY  - CONF
AU  - Xiaohong Yang
AU  - Faqing Tang
PY  - 2016/10
DA  - 2016/10
TI  - Wind Speed Forecast Based on Support Vector Machine
BT  - Proceedings of the 2016 5th International Conference on Civil, Architectural and Hydraulic Engineering (ICCAHE 2016)
PB  - Atlantis Press
SP  - 47
EP  - 51
SN  - 2352-5401
UR  - https://doi.org/10.2991/iccahe-16.2016.9
DO  - 10.2991/iccahe-16.2016.9
ID  - Yang2016/10
ER  -