A Method for Early Warning and Governance of Construction Engineering Data Based on Gaussian Mixture Model and EM Algorithm
The construction engineering industry plays an important economic and social role in modern society,however,it is also accompanied by many risks and uncertainties.In order to effectively manage and predict these risks,this paper proposes a data early warning governance approach based on Gaussian mixture model(GMM)and expectation maximization(EM)algorithm.This approach aims to improve the management and decision-making of engineering projects by modeling and analyzing construction engineering data to identify potential problems and risks in advance.
GMM Gaussian mixture modelEM algorithmdata early warning governancenormal distribution curveposterior probability
万方数据
维普
