Analysis of wind regimes for energy estimation in Bamenda, of the North West Region of Cameroon, based on the Weibull distribution
Bibliographic record
Abstract
The modelling and prediction of wind characteristics in a region is a primary requirement to the development of the corresponding wind energy system. This paper studies the wind energy potential for Bamenda in the North-West Region of Cameroon, with geographical coordinates: latitude 5.96°N, longitude 10.12°E and an elevation of 785 m. The analysis is based on data obtained from NASA surface meteorology and solar energy dataset for 11 years 1983 to 1993 through the RETScreen software tool provided by CANMET Canada. Through an analysis using the Weibull distribution function, the Weibull shape k, and scale c, parameters are determined using the least square graphical method to be 6.938 and 2.022 respectively. The mean wind speed, the variance, the standard deviation, the most probable /speed and the wind power density are also estimated characterising the wind regime of Bamenda. Comparing these results with the measured ones, it is shown that the Weibull distribution can be used with acceptable statistical accuracy for prediction of wind energy potential of Bamenda.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".