Prediction of daily global solar radiation by day of the year in four cities located in the sunny regions of Iran

By H. Khorasanizadeh, Kasra Mohammadi. 2013

76 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Environmental Engineering, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/d60ad5b8c147aa8937f65fa7d505a7a86ae71db2

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

1. Chong Wen Tong
2. Shahaboddin Shamshirband
3. Dalibor Petkovic
4. Kasra Mohammadi
5. Khubaib Amjad Alam
6. J. Almorox

In Environmental Engineering

1. Shahaboddin Shamshirband
2. Chong Wen Tong
3. Dalibor Petkovic
4. Khubaib Amjad Alam
5. Kasra Mohammadi

In Renewable Energy, Sustainability and the Environment

1. Shahaboddin Shamshirband
2. Chong Wen Tong
3. Dalibor Petkovic
4. Khubaib Amjad Alam
5. J. Almorox
6. 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): “Values of 0.015 and 1.00 as lower and upper thresholds of KT, respectively, are recommended by Jian (2009) and Khorasanizadeh et al. (2013).”
• Potential of adaptive neuro-fuzzy system for prediction of daily global solar radiation by day of the year (2015, methodology): “Khorasanizadeh and Mohammadi [25] assessed the performance of 6 DYB models to predict the daily global solar radiation in four cities situated in sunny regions of Iran.”