Research on Intelligent Optimisation Strategies for Interior Space Layout Design with the Aid of 3DsMax+AI

Abstract

Indoor intelligent assistive technology has been widely used in space layout design optimization. This paper proposes a heuristic scene space layout generation method based on the smart evolution of scene space AI with WFC and deep network, joint wave function collapse algorithm, as well as two deep neural networks to generate the layout wireframe diagram while strangling reasonable boundaries and predicting functional semantic labels for the layout subspace. Applying the method of this paper to the office space layout optimization design, the results show that 95.68% of the area of the office and conference room has a lighting coefficient greater than 2%, and 85.78% of the area of the design room has a lighting coefficient greater than 3%. Ordinary white glass can be utilized in the design room to enhance the lighting quality, with a lighting coefficient of 2.87 and a compliance rate of 100%. The inset atrium space has a greater percentage of indoor thermal comfort area and a faster air flow rate. In this paper, 3DsMax+AI intelligent assistance and other technologies are used to simulate the layout design of the office space and realize the optimization of its layout design.

Keywords

• deep network
• ai intelligent evolution
• wave function collapse
• space layout design
• 97p10