ANALYSIS OF THE APPLICATION OF MACHINE LEARNING METHODS IN THE CONSTRUCTION INDUSTRY

The theoretical and practical aspects of applying machine learning (ML) methods in the construction industry are considered, in which the increasing complexity of decision-making and the need to improve the efficiency of managing the lifecycle of capital construction projects drive the adoption of modern intelligent algorithms. The history of machine learning, its fundamentals, and existing ML methods arepresented. An analysis of the advantages and disadvantages of machine learning as a whole and of existing ML methods is conducted. A classification of machine learning methods is developed, tailored to the tasks addressed at various stages of the lifecycle of capital construction projects (engineering surveys, design, construction, operation, major repairs, reconstruction, and demolition). The conclusion highlights the high potential of applying machine learning in the construction industry to enhance prediction accuracy, optimize resource costs, and reduce risks at all stages of the lifecycle of capital construction projects.