An Application of Fuzzy Time Series: A Long Range Forecasting Method in the Global Steel Price Index Forecast
Why this work is in the frame
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Bibliographic record
Abstract
The global steel price index is a leading indicator in the bulk shipping industry. A study of the global steel price index combined with the establishment of fuzzy time series models can be used to predict future trends in the trading range of the global steel price index. Analysis of applied fuzzy time series data shows the following results: (1) Price volatility of the global steel price index remains positive following the global financial crisis; (2) Mode analysis shows that the 2012 global steel price index has a predictive value of 211.864 and its trading range will fluctuate between 74.577 and 211.864; (3) The group average prediction error rate is 4.40%. This paper describes the results of a study that can provide reference data to investors for hedging purposes and to operators in the shipping industry.
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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 | 0.009 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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