Wind Energy Assessment at Bafoussam, Cameroon
Bibliographic record
Abstract
Three-hourly wind speed data measured using the Beaufort scale at a height of 10m, from 6am to 6pm local time (5 periods per day), was obtained from the Bafoussam Airport. It was analyzed using the Weibull and Rayleigh probability density models and wind rose plots. It was determined that the lowest wind speeds (most calms) were observed during the first period (6am) and the highest at 3pm (fourth period). The very low morning wind speed adversely affected the daily mean wind speed. Better, but still poor, power density results were obtained at this fourth (3pm) period. The monthly and yearly mean speeds varied between 1.9 and 3.1m/s and with very low standard deviations. The wind rose plots also showed that all the significant winds fell in the first quadrant (NE) and predominantly on angle 10o with some discernibly on 20o and 30o, only. Three goodness-of-fit tests: the chi square, coefficient of determination or R2 and root mean square error, showed the Weibull to be a better fit to the wind regime than the Rayleigh model. The shape parameters were always greater than the scale parameters. Results show that, using the Weibull parameters, the power density of Bafoussam falls in the category 1 of the wind energy resource group and hence is not a very good wind energy exploitable candidate.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".