Modified artificial bee colony algorithm for optimal distributed generation sizing and allocation in distribution systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper presents a modification in the neighboring search of the artificial bee colony (ABC) algorithm. The ABC algorithm is a new meta-heuristic population-based optimization technique inspired by the intelligent foraging behavior of honeybee swarms. To verify the validity of the proposed modified ABC algorithm, the problem of determining the optimal size, location and power factor for a distributed generation (DG) to minimize total system real power loss is considered. The IEEE 33-bus and 69-bus feeder systems are examined, and the results obtained by the proposed algorithm are compared with those found using other methods. The outcomes verify that the modified ABC algorithm has excellent solution quality and convergence characteristics. The efficiency of the proposed algorithm lies in the fact that the standard deviation of the attained results for 30 independent runs at every test case is virtually equal to zero.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 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) | 0.000 | 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 it