Evaluation of Solar Radiation Prediction Models in North America

By R. Ball, L. C. Purcell, S. Carey. 2004

105 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/56920f467933e7761718522fce3df58275585b52

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. Jeffrey T. Edwards
2. Earl Vories
3. Ali Assi
4. Hassan A. N. Hejase
5. L. C. Purcell

In Renewable Energy, Sustainability and the Environment

1. Jeffrey T. Edwards
2. Earl Vories
3. Ali Assi
4. Hassan A. N. Hejase
5. L. C. Purcell

Citations in the corpus

• Light Interception and Yield Potential of Short‐Season Maize ( Zea mays L.) Hybrids in the Midsouth (2005, methodology): “Ball et al. (2004) found that this method of es- interaction with temperature and photoperiod. timating solar radiation agreed well with observed values over Irrigation requirements were considerably less for thea wide geographical region without a need for site-specific calishortest-season hybrids…”
• Time-Series Regression Model for Prediction of Mean Daily Global Solar Radiation in Al-Ain, UAE (2012, background): “Numerous authors [2–24] developed empirical regressionmodels to predict themonthly average daily GSR in their region using various parameters.”