Distributed photovoltaic index insurance premium prediction method based on ARIMA model
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
Photovoltaic power generation is an important field of the current new energy development, and distributed photovoltaic mode has gradually become an important trend in the development of the photovoltaic industry, for the distributed photovoltaic industry in China's domestic development status, there is an urgent need for a new kind of insurance products, to support photovoltaic enterprises to promote the development of the industry. ARIMA distributed PV and index insurance are reviewed. After researching and synthesizing the mature power generation index insurance in foreign countries, this paper collects 57 distributed PV projects and takes the GHI data of distributed PV projects in Shaoxing City, Zhejiang Province, as a representative, obtains the GHI data from NASA, and explores the process and significance of constructing the power generation index insurance model based on ARIMA model by using the method of machine science.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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