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Record W4409787735 · doi:10.61091/jcmcc127a-522

Research on the Innovation of Rattan Weaving Art Design Form and Inheritance of Cultural Symbols of Maonan Flower Bamboo Hat Based on Complex Geometry and AI Algorithm

2025· article· en· W4409787735 on OpenAlexvenueno aff

Bibliographic record

VenueJournal of Combinatorial Mathematics and Combinatorial Computing · 2025
Typearticle
Languageen
FieldComputer Science
TopicDigital Media and Visual Art
Canadian institutionsnot available
Fundersnot available
KeywordsWeavingRattanInheritance (genetic algorithm)BambooFashion designGeometryMathematicsAlgorithmEngineeringGeographyBotanyArchaeologyMechanical engineeringMaterials scienceComposite material

Abstract

fetched live from OpenAlex

The field of artificial intelligence provides a new practical path for the inheritance and protection of non-heritage art.This paper proposes an innovative morphological design method for rattan weaving art based on fractal theory, and the grasshopper plug-in is selected to establish a parametric design model.The fractal graphics generated by the iterative function system are used as the input graphics, and the GrabCut algorithm and VGG16 neural network are combined to propose a graphic rendering method based on style migration containing elements of the cultural symbols of the Maonan Flower Bamboo Hat, and to realize the inheritance of the cultural symbols of the Maonan Flower Bamboo Hat.In the high preference survey, the A1 and A4 features of the sun hat in the questionnaire results are consistent with the preference results derived from the fractal design, and the questionnaire results of the handbag and handkerchief are also consistent with the preference results derived from the fractal design.It shows that the product form design method of Maonan flower bamboo hat cultural symbols based on fractal theory and style migration can play a certain role in promoting cultural inheritance.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.060
GPT teacher head0.348
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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