###### Abstract
[6] used the Analytic Hierarchy Process (AHP) and Criteria Importance Through Inter-criteria Correlation (CRITIC) method to evaluate the fire resilience of ancient buildings. [PERSON] et al. [7] analyzed the systematic approach of sustainable urban response to climate from the perspective of urban planning, thereby improving urban resilience, while [PERSON] et al. [8] identified the key influencing factors for station resilience against heavy rain disasters using the Interpretive Structural Model method (ISM) with the Social Network Analysis method (SNA).The ISM method can make up for the shortcomings of the above research and give full consideration to the interaction between various factors, but it ignores the determination of key factors. Most research methods on influencing factors in the existing literature struggle to effectively identify key factors and their pathways of influence. Currently, limited research has addressed wind resilience specifically in the context of historical districts. Existing studies tend to focus on the impacts of typhoons on individual historical buildings, communities, or villages in coastal regions, rather than on integrated historical blocks. [PERSON] et al. [9] examined historical villages and dwellings in the Leizhou Peninsula, one of mainland China's most typhoon-prone regions, to explore adaptive design strategies for coping with typhoon climates. Their study proposed practical measures to enhance the wind resilience of historical settlements in coastal areas vulnerable to such extreme weather events. [PERSON] et al. [10] assessed the vulnerability of traditional wooden houses in Madagascar's eastern coastal regions to extreme wind events and developed a model to evaluate their wind-related structural weaknesses. [PERSON] et al. [11] developed a comprehensive framework to assess the resilience of coastal communities under various hurricane scenarios, considering both social and physical dimensions. By simulating potential damage and economic losses to community infrastructure, the framework supports decision-makers in formulating strategies to enhance the resilience of these vulnerable areas. Because of the complex interplay of factors influencing wind resilience in coastal historical districts, few studies have adopted a systematic, integrated approach to analyze these elements. As a result, the depth and focus of existing research in this area remain limited [12-25]. In view of this, in order to effectively clarify the influencing factors and action paths of wind resilience of China's coastal historical districts, this study evaluated the impact intensity of the factorsaffecting wind resilience of China's coastal historical districts, and clarified the internal connections and hierarchical structures among the factors, so as to provide corresponding suggestions in order to improve the wind resilience of China's coastal historical districts. In order to accurately identify the main influencing factors of the wind resilience of China's coastal historical districts, this study proposed the IDEMATEL method based on the Decision Experimentation and Evaluation Laboratory (DEMATEL) method. DEMATEL is a method used to solve system factor analysis. The principle of this method is to combine graph theory with matrix theory to judge the importance of each factor in the system [26]. The core of improving the DEMATEL method is to select more reasonable research indicators to establish a more convincing set of influencing factors. The process for the method improvement is as follows: First, preliminary indicator data is collected through the Web of Science and Science Direct databases, and the indicators that appear frequently in related studies are summarized. Then, a two-round expert questionnaire survey method is used to score the indicators, and the reliability and validity tests of the expert scoring results are performed to screen the indicators and determine the final set of influencing factors.