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<p>To be able to protect the historical culture better and cater to public preferences, this paper proposes the innovative inheritance of Guangxi minority costume design under rural revitalization. According to the object similarity shift, make all the objective function values reach predetermined values, iteratively calculate new clustering centers, and select initial values so that the minimal local values converge. Using Euclidean distance to calculate the distance between objects and divide them into corresponding clusters, we continuously process the data set and complexity to ensure that no clustering bias is formed. The curve relationship is constructed through a nonlinear function to reflect the possible probability change of clothing innovation and inheritance events, and the function is logarithmically transformed to increase the probability of occurrence of ethnic clothing innovation and inheritance under rural revitalization. The nonlinear relationship was transformed into a linear one so that the variables conformed to the normal distribution, and the clothing design innovation inheritance under rural revitalization was extracted. The analysis of the results shows that ethnic elements have a greater influence on contemporary product design under the perspective of rural revitalization, and the algorithm proposed in this paper has a high accuracy rate of 65% for the study of clothing design.</p>
</abstract>

To be able to protect the historical culture better and cater to public preferences, this paper proposes the innovative inheritance of Guangxi minority costume design under rural revitalization. According to the object similarity shift, make all the objective function values reach predetermined values, iteratively calculate new clustering centers, and select initial values so that the minimal local values converge. Using Euclidean distance to calculate the distance between objects and divide them into corresponding clusters, we continuously process the data set and complexity to ensure that no clustering bias is formed. The curve relationship is constructed through a nonlinear function to reflect the possible probability change of clothing innovation and inheritance events, and the function is logarithmically transformed to increase the probability of occurrence of ethnic clothing innovation and inheritance under rural revitalization. The nonlinear relationship was transformed into a linear one so that the variables conformed to the normal distribution, and the clothing design innovation inheritance under rural revitalization was extracted. The analysis of the results shows that ethnic elements have a greater influence on contemporary product design under the perspective of rural revitalization, and the algorithm proposed in this paper has a high accuracy rate of 65% for the study of clothing design.

Research on the innovative inheritance application of Guangxi minority elements in clothing design under the perspective of rural revitalization

Guangxi University of Science and Technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

To be able to protect the historical culture better and cater to public preferences, this paper proposes the innovative inheritance of Guangxi minority costume...

Research on the innovative inheritance application of Guangxi minority elements in clothing design under the perspective of rural revitalization

Online veröffentlicht: 09. Juni 2023

Seitenbereich: -

Eingereicht: 21. Juni 2022

Akzeptiert: 15. Dez. 2022

DOI: https://doi.org/10.2478/amns.2023.1.00384

Schlüsselwörter
Rural revitalization, Minority elements, Innovative heritage, K-Means algorithm, Logistic regression model

© 2023 Jianyun Yan et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on the innovative inheritance application of Guangxi minority elements in clothing design under the perspective of rural revitalization

Online veröffentlicht: 09. Juni 2023

Seitenbereich: -

Eingereicht: 21. Juni 2022

Akzeptiert: 15. Dez. 2022

DOI: https://doi.org/10.2478/amns.2023.1.00384

SchlüsselwörterRural revitalization, Minority elements, Innovative heritage, K-Means algorithm, Logistic regression model

© 2023 Jianyun Yan et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Rural revitalization, Minority elements, Innovative heritage, K-Means algorithm, Logistic regression model