Support Vector Regression Based on Grid-Search Method for Short-Term Wind Power Forecasting
The purpose of this paper is to investigate the short-term wind power forecasting. STWPF is a typically complex issue, because it is affected by many factors such as wind speed, wind direction, and humidity. This paper attempts to provide a reference strategy for STWPF and to solve the problems in e...
Main Authors: | Hong Zhang, Lixing Chen, Yong Qu, Guo Zhao, Zhenwei Guo |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2014-01-01
|
Series: | Journal of Applied Mathematics |
Online Access: | http://dx.doi.org/10.1155/2014/835791 |
Similar Items
-
Forecasting Short-Term Power Output of Photovoltaic Systems Based on Support Vector Regression
by: Yi-Song Lin, et al.
Published: (2019) -
Short-Term Wind Speed Forecasting Using Support Vector Regression Optimized by Cuckoo Optimization Algorithm
by: Jianzhou Wang, et al.
Published: (2015-01-01) -
Hybrid Empirical Mode Decomposition with Support Vector Regression Model for Short Term Load Forecasting
by: Wei-Chiang Hong, et al.
Published: (2019-03-01) -
Short Term Wind Power Prediction Based on Data Regression and Enhanced Support Vector Machine
by: Chia-Sheng Tu, et al.
Published: (2020-11-01) -
Hybrid ARIMA and Support Vector Regression in Short‑term Electricity Price Forecasting
by: Jindřich Pokora
Published: (2017-01-01)