A method of electricity consumption behaviour clustering and pricing packages based on data mining
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
In this paper, under the background of the reform of electricity sales side, a method of electricity consumption behaviour clustering and pricing packages based on data mining is proposed. Firstly, a distributed clustering framework combining DTW k-medoids algorithm and CFSFDP algorithm is proposed. Secondly, typical load curves of local data are extracted under the framework to construct local model. Then, quadratic clustering analysis is carried out for the local model results, and the global typical load curve is obtained to construct the global model. Finally, recommend the most suitable electricity sales plan to the target users. The experimental result shows that the subdivision of electricity consumption behavior can realize the effective personalized electricity package recommendation service for users and improve the power supply service quality for power companies and provide technical support for improving the operation efficiency.
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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 | 0.001 | 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 | 0.001 |
| 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