ASPECTS OF USING GENERATIVE NEURAL NETWORKS FOR DESIGN PROJECTS

Abstract

This article explores the key aspects of using neural networks in architectural and interior design. The advantages of generative adversarial networks (GANs) in this field are discussed. Based on prompts, various images of a mountain chalet and its interior design were generated. Seamless textures were also created using the Midjourney neural network. Using the same neural network, furniture textures and posters were produced for 3D visualization of an apartment in SketchUp. This work aims to provide a comprehensive study of neural networks' application in design projects. To achieve this, it is necessary to analyze the current state of research in this field, identify the main development directions, and identify existing issues. The study describes various ways of using neural networks in architecture and interior design, evaluates the potential benefits and risks of their application, and develops recommendations for the effective use of neural networks in architectural and interior design practice. Methodology. The article uses theoretical methods of literature review, testing, and comprehensive analysis of the capabilities of modern neural networks, as well as empirical methods for studying the use of neural networks in design projects. Scientific novelty lies in the adaptation of modern approaches to the use of neural networks for the generation of architectural projects and interior design. Conclusions. The use of neural networks in architectural design as well as in interior and exterior design is becoming increasingly widespread. The development of generative image creation is progressing rapidly and is being actively applied in these fields. AI-based editing tools are being integrated into more and more well-known design programs and require preliminary analysis and study to develop specific recommendations for their use. This work provides a detailed analysis of future development directions of AI-based networks and proposes practical tools for their implementation.