A statistical comparative study to demonstrate the merit of day of the year-based models for estimation of horizontal global solar radiation
By H. Khorasanizadeh, Kasra Mohammadi, Mahdi Jalilvand. 2014
53 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Renewable Energy, Sustainability and the Environment
View Paper: https://www.semanticscholar.org/paper/a3a923af5df34d52ef56caace90e8462f1e24c4f
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
- Chong Wen Tong
- Shahaboddin Shamshirband
- Dalibor Petkovic
- Kasra Mohammadi
- Sudheer Ch
- Khubaib Amjad Alam
- J. Almorox
- Muhammad Arif
In Renewable Energy, Sustainability and the Environment
- Shahaboddin Shamshirband
- Chong Wen Tong
- Dalibor Petkovic
- Khubaib Amjad Alam
- Sudheer Ch
- J. Almorox
- Kasra Mohammadi
Citations in the corpus
- Estimating daily global solar radiation by day of the year in six cities located in the Yucatán Peninsula, Mexico (2017, background): “Recently, some studies have been aimed at developing and establishing simple models to estimate global solar radiation without meteorological data using the day of the year as the sole independent parameter, hereinafter referred as day of the year-based (DYB) models (Khorasanizadeh et al., 2014).”
- A new hybrid support vector machine–wavelet transform approach for estimation of horizontal global solar radiation (2015, methodology): “Additionally, for a month with less than 5 days the missing or inaccurate values were substituted by proper values obtained using interpolation [43,44].”
- Potential of adaptive neuro-fuzzy system for prediction of daily global solar radiation by day of the year (2015, methodology): “[26] performed an investigation to assess the merit of DYB models by providing statistical comparisons with different sunshine duration-based and temperature-based models.”