Analysis of Regional Characteristics of Jinnan Folk Paper-cutting by Dynamic Programming Algorithm

Main Article Content

Jimin Li
Guoyun Zhang

Abstract

The role of regional characteristics analysis in the development of folk paper-cutting in southern Jinnan makes folk paper-cutting change regionally, and also makes Jinnan folk paper-cutting a hot spot. However, in the process of analyzing the folk paper-cutting area, there are problems such as poor analysis effect and a small amount of analysis data. The main reason is that the wireless network technology in the southern Jinnan region is backward, which restricts the development of folk paper cutting. Therefore, this paper proposes a folk paper-cutting feature analysis method based on a dynamic programming method to plan the characteristics of folklore paper-cutting in different regions. Firstly, collaborative wireless communication technology is used to collect folk paper-cutting data, and the data of different regions are summarized by dynamic programming method, and the regional division of papercutting is carried out according to the characteristics of folklore, leaving common characteristics. Then, according to dynamic call wireless communication technology, the transmission of regional characteristics is carried out to promote the integration of the characteristics of folk paper cutting. The results of the regional characteristic analysis show that with the support of collaborative wireless communication, the dynamic programming method can improve the level of folk paper-cutting in southern Jinnan, and promote the development of paper-cutting culture by using collaborative wireless network communication, can meet the requirements of Jinnan cultural construction.

Article Details

How to Cite
Jimin Li, & Guoyun Zhang. (2023). Analysis of Regional Characteristics of Jinnan Folk Paper-cutting by Dynamic Programming Algorithm. International Journal of Communication Networks and Information Security (IJCNIS), 15(2), 51–62. https://doi.org/10.17762/ijcnis.v15i2.5983
Section
Research Articles