Research on the Variable Fuzzy Evaluation Model of Ecotourism Resources in National Parks from a Big Data Perspective

Abstract

The application of big data technology in ecological resource management in national parks has led to changes in its evaluation index system and evaluation methods. Due to the large volume of data involved in the evaluation process of national park ecotourism resources, which covers a wide range, data characteristics such as strong timeliness, rapid environmental changes, and incomplete data exhibit fuzziness and uncertainty, traditional evaluation methods are unable to effectively address these issues. The theory of variable fuzzy sets can more effectively depict and quantify the uncertain changes of ecotourism resources in national parks. Therefore, this study employs the Semantic Differential (SD) method to quantify qualitative textual data, integrates it into big data indicators, and applies game theory integrated with the G1 method and the CRITIC method to determine subjective and objective weights. Consequently, a variable fuzzy evaluation model for ecotourism resources in national parks is constructed. Additionally, using Qianjiangyuan National Park as an example, the effectiveness and reliability of this model method are verified through a case study. This model can provide a reference for research and application in this field and other domain.