Spatiotemporal interpolation and forecast of irradiance data using Kriging

By M. Jamaly, Jan Kleissl. 2017

47 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/35e69dbbc2903939560bab5a89fdb0201718a04c

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. H. Pedro
2. Dazhi Yang
3. Carlos F. M. Coimbra
4. Jan Kleissl
5. Christian A. Gueymard
6. Clifford W. Hansen
7. Matthew J. Reno
8. Joshua S. Stein

In Renewable Energy, Sustainability and the Environment

1. H. Pedro
2. Dazhi Yang
3. Jan Kleissl
4. Carlos F. M. Coimbra
5. Christian A. Gueymard
6. Ricardo Marquez
7. D. Thevenard
8. S. Pelland

Citations in the corpus

• History and trends in solar irradiance and PV power forecasting: A preliminary assessment and review using text mining (2018, methodology): “It has been applied several times in solar forecasting (e.g., Jamaly and Kleissl, 2017; Perez et al., 2016; Aryaputera et al., 2015b; Yang et al., 2014a, 2013b).”