A wavelet-coupled support vector machine model for forecasting global incident solar radiation using limited meteorological dataset
By Ravinesh C. Deo, Xiaohu Wen, F. Qi. 2016
339 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment
View Paper: https://www.semanticscholar.org/paper/fa7885fb4000c2bd6d855b3e6ae56f2af5dcdbf0
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- H. Pedro
- Dazhi Yang
- Carlos F. M. Coimbra
- Jan Kleissl
- Ping-Huan Kuo
- Chiou-Jye Huang
- Qi Feng
- Xiaohu Wen
In Electrical and Electronic Engineering
- Ping-Huan Kuo
- Chiou-Jye Huang
- Ravinesh C. Deo
- Xiaohu Wen
- Carlos F. M. Coimbra
- Zhi-bin He
- Jianhua Si
- Dazhi Yang
In Renewable Energy, Sustainability and the Environment
- H. Pedro
- Ping-Huan Kuo
- Chiou-Jye Huang
- Dazhi Yang
- Ravinesh C. Deo
- Jan Kleissl
- Carlos F. M. Coimbra
- Christian A. Gueymard
Citations in the corpus
- Design and evaluation of SVR, MARS and M5Tree models for 1, 2 and 3-day lead time forecasting of river flow data in a semiarid mountainous catchment (2018, methodology): “For an optimal design of SVR model, a grid search procedure, as used in previous studies, was applied (Deo et al. 2016; Hsu et al. 2003) where the most accurate value for the penalty C, and the radial basis function’s kernel, c (Eqs.”
- A High Precision Artificial Neural Networks Model for Short-Term Energy Load Forecasting (2018, methodology): “A novel approach based on the support vector machine was proposed in [26,27].”
- History and trends in solar irradiance and PV power forecasting: A preliminary assessment and review using text mining (2018, positive): “, 2006), and wavelet-coupled SVM, which decomposes the input signal before applying SVM to produce forecasts (Deo et al., 2016).”