Application of fuzzy clustering based on improved whitening weight function in vocational education evaluation

In recent years, the importance of vocational education development has increased significantly. The key to improving vocational education lies in addressing the evaluation problem of vocational education schools. However, previous solutions to this problem suffered from issues like subjective evaluation methods and distorted data. This paper presents a vocational education evaluation method that combines gray clustering and fuzzy clustering, while also improving the form of the whitening weight function. The initial membership degree is calculated using the whitening weight function, followed by optimization using fuzzy C-means clustering. Experimental results demonstrate that this algorithm effectively combines the advantages of gray clustering and fuzzy C-means clustering, enabling more accurate clustering of vocational education schools in the evaluation process. This approach facilitates more objective evaluation and provides a quantitative basis for vocational education evaluation.