Fuzzy measurements of power system symmetrical components
Bibliographic record
Abstract
The symmetrical components are an effective tool for the analysis of the unsymmetrical fault in the power systems. Also, it can be used as an indication to abnormal normal operation of power systems. This paper presents the application of fuzzy system to measure the symmetrical components of a power system for control and protection. The samples for the symmetrical components are obtained using the symmetrical transformation matrix in the time domain. Then the problem of the symmetrical component parameters is formulated as a linear fuzzy regression problem to estimate the fuzzy parameters of each component from the available samples. Two models are discussed in this paper, while in the first model, we assume that the data samples are non-fuzzy, and the model coefficients are fuzzy. In the second model, we assume the data samples are fuzzy and the model parameters are fuzzy as well. The simplex-based linear programming method is used to solve the resulting problems. Simulated and actual recorded data are presented in the paper.
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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 | 0.000 | 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 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".