关键词: 施工安全评价, 因子分析, 变分贝叶斯高斯混合模型, 可视化, 聚类

Abstract: With the continuous increase of construction needs, the problem of construction safety is becoming more and more complex. In order to further decrease the occurrence of construction safety accidents, the traditional safety evaluation methods cannot effectively excavate the internal connection between the safety indicators. Besides, the existing clustering methods have the problems of insufficient compactness and poor interpretation. Therefore, this paper presents a safety evaluation method using factor analysis and variational Bayesian Gaussians mixture model, which adopts factor analysis to convert complex construction safety evaluation indicators into internally related factor variables as the inputs of variational Bayesian Gaussians mixture method. The multidimensional clustering results are visualized using the T-distributed stochastic neighbor embedding (T-SNE) method, so as to fully explore the intrinsic correlation between various construction safety indicators and evaluate construction safety. Case analysis shows that compared with hierarchical clustering analysis, K-means and Gaussian mixture model (GMM) method, the proposed method has better clustering effect and global optimization performance. It not only verifies the feasibility and effectiveness of the proposed method, but also improves the interpretability of multidimensional clustering problems by visualization method.