## 5 Conclusions  
In this article, through the analysis of existing algorithms and their improvement methods based on the type of mountainous terrain with high relief in complex landscapes, the uncertainty of internal nodes in Delaunay triangulation, and the problem of good and bad mesh quality, the TCOGIM algorithm is proposed to be applied to assist in the improvement of mountainous terrain with high relief in complex landscapes, combined with the B-W algorithm, which provides a method to efficiently and accurately analyzing and calculating the mesh in studying the distribution of wind resources in mountainous terrain. The method employed for mesh delineation involves comparing it with the average value of the boundary triangles' area to determine the necessity of interpolating the center of gravity for increased internal nodes. This process is then coupled with the B-W algorithm to reconstruct the triangles to cycle judgment on the newly generated triangle unit area. This cycle continues until all triangles meet the conditions, satisfying the Delaunay criterion and generating a Delaunay triangular mesh. Through simulation combined with an actual wind farm application in Yunnan Province, we compare the triangular mesh in the same region generated by the Delaunay-TCOGIM algorithm with that produced by the Delaunay method in terms of metrics, such as mesh quality coefficient and mesh regularity, as well as the CPU running time of the two algorithms. The comparison results show that the Delaunay-TCOGIM algorithm exhibits better applicability to complex terrain with high elevation differences. It effectively enhances the quality of the Delaunay triangular mesh, mitigates the generation of distorted grid cells, and improves the efficiency of grid generation. However, when choosing the number of loops and the multiplier, we should choose a reasonable value to avoid the calculation time being too long, which affects the efficiency. Moreover, the results of making changes to this wind farm's contour discrete point set show that after reducing the selection of part of the contour discrete points, the triangular mesh can be made more efficiently. The results show that after reducing the selection of some contour discrete points, the more refined the triangular grid cells are, the better the grid quality is. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Number of** & **Number of Discrete Points** & **Number of Discrete Points** & **Running Time of This** & **Running Time of** \\
**Cycles/Times** & **of This Algorithm** & **of Delaunay Method** & **Algorithm/s** & **Delaunay Method/s** \\ \hline
1 & & 268 & & 8.86 & 8.94 \\
2 & & 427 & & 14.06 & 14.69 \\
3 & 450 & & 449 & 18.70 & 21.67 \\
4 & 457 & & 455 & 24.09 & 23.19 \\
5 & 459 & & 462 & 32.61 & 29.78 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: CPU runtime comparison. **Author Contributions:** W.Z., conceptualization, investigation, methodology, writing--original draft, and writing--review & editing; H.W., conceptualization, formal analysis, methodology, funding acquisition, and supervision; X.H., formal analysis, investigation, resources, supervision, and validation. All authors have read and agreed to the published version of the manuscript. **Funding:** This research was funded by the Tianshan Talent Project of Xinjiang Uygur Autonomous Region, grant number 2022 TSYCJC0030, the Key Research and Development Project of Xinjiang Uygur Autonomous Region, grant number 2022B03031, and the Hami High-tech Zone Science and Technology Project, grant number HGX2023 KJXM008. **Institutional Review Board Statement:** Not applicable. **Informed Consent Statement:** Not applicable. **Data Availability Statement:** The raw data supporting the conclusions of this article will be made available by the authors on request. **Conflicts of Interest:** Author [PERSON] was employed by the company Goldwind Science & Technology Co., Ltd.