An indicator of solar radiation model performance based on a fuzzy expert system
By Gianni Bellocchi, Marco Acutis, G. Fila, Marcello Donatelli. 2002
117 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Management Science and Operations Research, Renewable Energy, Sustainability and the Environment
View Paper: https://www.semanticscholar.org/paper/92559a2484d875bde19697750b02dae8379fb343
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- I. Abustan
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- Xin Li
- Ling Lu
Citations in the corpus
- The Soil Management Assessment Framework (2004, unknown): “In addition, a SQ assessment tool needs to interpret the indicators of those functions in The SMAF uses a series of decision rules (Bellocchi et al., 2002; Schadt et al., 2002), in a database format, to generate terms of the inherent abilities of the soil and climate in a list of suggested MDS…”
- Estimating near future regional corn yields by integrating multi-source observations into a crop growth model (2013, methodology): “model calibration: the mean residual error (ME), the mean relative error (MRE), the mean absolute error (MAE) and the root mean square error (RMSE) (Smith et al., 1996; Bellocchi et al., 2002; Donatelli et al., 2004).”
- A new novel index for evaluating model performance (2014, background): “Bellocchi et al. (2002) proposed a fuzzy expert system to calculate a composite indicator for performance evaluation of solar radiation.”