Blockchain-Based Intelligent Transportation: A Sustainable GCU Application System
Bibliographic record
Abstract
The purpose of this study is to explore how to apply blockchain technology to intelligent transportation, create a hierarchical theoretical framework of intelligent transportation, and explore a sustainable application system of intelligent transportation under the blockchain. However, not only this hierarchical theoretical framework must consider unnecessary attributes and the interrelationships between the aspects and the criteria, but also the sustainable application system must be in consideration in multiple stakeholders. Hence, fuzzy set theory is used for screening out the unnecessary attributes, a decision-making trial and evaluation laboratory (DEMATEL) is proposed to manage the complex interrelationships among the aspects and attributes, and interpretive structural modeling (ISM) is used to divide the hierarchy and construct a hierarchical theoretical framework. Finally, the research develops a sustainable GCU application system for intelligent transportation under the blockchain. The results show that (1) solving social problems is the primary link, (2) economic tasks are mainly focused on smart contracts and affected by the social problems, (3) the continuous improvement of environmental issues requires a solution to social problems, and (4) the application system of blockchain in intelligent transportation needs to be built from three levels including the government layer, the company layer, and the user layer. This theoretical hierarchical framework aims to guide intelligent transportation toward the application of blockchain. This study also proposes the engagement of stakeholders for establishing a sustainable application system.
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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 | 0.001 |
| 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 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".