Digital conservation and inheritance strategies of folk traditional crafts based on Light GBM model

Abstract

The role of digital technology in cultural heritage conservation should be diverse, and different types of traditional handicrafts should be protected using appropriate digital technology. In this paper, the Light GBM algorithm is used to reduce the total number of large samples and lower the level of representation to solve the correlation problem between large-scale statistical instances and large sample features, and improve the prediction efficiency and accuracy of the algorithm. The algorithm of this paper predicts the effect of traditional handicrafts in the Wuling ethnic region of China under various digital technologies, and the results of Enshu Yulu making and bamboo paper making using digital image processing technology are obtained. The best results were 73.17% and 89.38% for the production of Enshu and bamboo paper, 88.26% for the printing of blue printed cloth, 85.24% and 78.67% for the production of Miao silver ornaments and Yuping flute, 91.54% for the production of Dong brocade, and 91.65% for the construction of Tujia hanging foot tower using digital sand table. The best effect of using digital sand table technology for the creation of the Tujia hanging foot tower reached 91.65%. Therefore, the algorithm in this paper can match the appropriate digital technology for different types of traditional handicrafts to achieve a greater degree of preservation and inheritance.