Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 9, Issue 1


Published
on

September 3, 2024


Pages


DOI

Article

Predicting the future trend of cultural revitalization of traditional Hakka villages in western Fujian in the context of rural revitalization using machine learning

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Authors

Rong Zhang Affiliation:
Sanming University, Sanming, Fujian, 353000, China.
and Yuhua Lin Affiliation:
Sanming University, Sanming, Fujian, 353000, China.


Abstract

The “revitalization” development of traditional village culture is more embodied as the revitalization of the “traditional village cultural landscape genes.” This paper combines the overall concept and development strategy for the protection and development of traditional Hakka villages in western Fujian and puts forward the path of “revitalization” development of traditional Hakka villages in western Fujian. “Revitalization” development path. Construct a cultural development prediction based on the grayscale GM (1,1) model and test its accuracy by combining it with the GDP value of eight counties in western Fujian (Longyan City). Analyze the Hakka cultural tourism resources and major source markets in western Fujian and use the grayscale GM (1,1) model to make a future development prediction for the development of the Hakka traditional village culture industry in western Fujian. The GM(1,1) model’s absolute value for both relative error and rank deviation is less than 0.1. When combined with the grayscale GM(1,1) prediction model, we expect the culture of Hakka traditional villages in western Fujian to generate approximately 59024 million yuan in cultural tourism revenue by 2027.


Keywords

Prediction model, GM(1, 1) model, Tourism development, Western Fujian Hakka culture, 68M11


Citation

Zhang, R. & Lin, Y. (2024). Predicting the future trend of cultural revitalization of traditional hakka villages in western fujian in the context of rural revitalization using machine learning. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-2447
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