CS-SVM Algorithm Empowers BIM Technology in the Model Construction and Application of Construction Project Cost Prediction

In traditional construction project cost prediction, there are often challenges such as poor adaptability to complex projects and unsatisfactory prediction accuracy. In view of this, this paper innovatively constructs a cost prediction model based on CS-SVM. It deeply analyzes the Cuckoo Search Algorithm (CS) and uses it to optimize the Support Vector Machine (SVM), thus creating a CS-SVM model with excellent parameter optimization performance. The cost data of cloud computing projects are standardized to accurately determine the input variables. Combined with practical cases, the application effectiveness of the BIM construction project cost prediction model based on the CS-SVM algorithm is mainly tested. The results show that this model is accurate in construction project cost prediction, can effectively empower cost management, its application effect is significantly better than other models, and it has great promotion value, playing a key guiding role in optimizing the construction project cost prediction method.