USING NEURAL NETWORK TECHNOLOGY IN CONSTRUCTION ACTIVITIES
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Abstract
The article discusses the basics of using neural networks in the activities of construction organizations. The main goal of the study was to substantiate the advantages and prospects of using neural networks in the construction industry. As part of the study, the essence of this variant of machine learning was initially determined, their classical architecture was justified, key elements were identified, and the principle of operation was described. Subsequently, options for using neural networks within the construction industry were systematized (design of construction projects, analysis of costs for the implementation of construction projects, management of construction projects, monitoring of labor and equipment productivity, assessment of the quality of materials used and inventory management, ensuring energy efficiency, risk analysis and ensuring the safety of work performed, etc.) and a distinction was made between the areas of application of neural networks within the stages of the life cycle of construction projects, which formed the basis of scientific novelty.
The results of the study can be applied in the activities of construction organizations to increase the efficiency of work carried out at various stages of construction.
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