Simplified Independent Model for Predicting Global Solar Radiation
Bibliographic record
Abstract
In this investigation, five existing independent empirical models were calibrated and evaluated to calculate daily and monthly mean global solar radiation on a horizontal surface in Adrar city located in the south of Algeria, using meteorological data measured from 2013 to 2018. The measured data were divided into two periods; the first period (2015-2018) was used to calculate the empirical coefficients of the models, while the second period (2013-2014) was used to validate the correlations. Additionally, the best model (Al-Salaymeh model) was compared with five dependent empirical extreme air temperature models. In general, the results show that dependent models exhibited privileged performance than independent models. However, Al-Salaymeh regression independent model can contend with regression dependent models. Because of they use only the day number as a key input with smaller relative errors. It is found that daily statistical tests mean absolute bias error, root mean square error and coefficient of determination were equal to 2.0117 MJ/m², 2.4612 MJ/m² and 0.8014 respectively. The best independent empirical model was also compared with the modified Algerian solar atlas model to show their effectiveness. As a conclusion, the simple independent models can satisfactorily describe the horizontal global solar radiation for Adrar.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".