Predictive analytics algorithms for building engineering system parameters

Abstract

The article discusses the relevance of deep learning methods using in predictive analytics of parameters of engineering systems in construction. The advantages and disadvantages of such methods are described, as well as the architecture of a cyberphysical type system based on machine learning for solving the problem of predictive analytics algorithms for building engineering system parameters. Conclusions are drawn about the applicability of the DBSCAN clustering algorithms, neural networks with the Attention mechanism and hierarchical trees ensembles within the research task.