Abstract
In order to explore the technical path of using artificial intelligence deep learning algorithm in realizing the interior space layout, this study introduces neural network modules such as 3D spatial convolutional (3DSC) neural networks and fuzzy neural networks (FNN), and a deep learning algorithm of indoor spatial layout design (ISLD) based on the adversarial neural network (ANN) is formed. In the algorithm design, a controllable data-interference adverse variation algorithm based on a random number generator is introduced, to obtain the data variant optimization process of genetic algorithm in neural network deep learning. As shown in the simulation analysis, the algorithm yielded significantly better subjective audience evaluation than other algorithms mentioned in references, and because it can be run offline on a single PC workstation, the demand for network resources and computing power resources is relatively small, so under the premise of the same hardware facility investment, higher production capacity can be obtained to get a higher input-output ratio, and it has a certain industry-university-research transformation and market promotion value.
Highlights
Layout design refers to the combination of dividing a given space into some small spaces or reasonably arranging several objects to be arranged in the space, meeting the constraints of some objective and subjective layout conventions and design criteria, and making the layout meet the customer’s satisfaction through optimization and adjustment [1]
Because home decoration design belongs to the category of engineering art design, the participation of artificial intelligence algorithm in art design has always been the biggest difficulty
Relevant research found that the deep learning function of artificial intelligence algorithm cannot participate in the whole process of home decoration design, it has certain usability in spatial layout design
Summary
Layout design refers to the combination of dividing a given space into some small spaces or reasonably arranging several objects to be arranged in the space, meeting the constraints of some objective and subjective layout conventions and design criteria, and making the layout meet the customer’s satisfaction through optimization and adjustment [1]. Relevant research found that the deep learning function of artificial intelligence algorithm cannot participate in the whole process of home decoration design, it has certain usability in spatial layout design. 2. Interior Space Layout Countermeasure Neural Network Design Based on Deep Learning. Interior Space Layout Countermeasure Neural Network Design Based on Deep Learning At this stage, with the gradual maturity and rapid popularization of artificial intelligence, the research on layout design is increasing. After deep neural network learning, the customer inputs the specified conditions to generate the qualified indoor space layout design drawing. We collected a large number of CAD indoor layout plans as data sets, entered the three-dimensional space convolution model, trained the logarithmic depth iterative convolution model through the polynomial regression model, and generated the selected indoor space layout design according to the conditions specified by the customer. The original CAD threedimensional model data are reread. e original CAD 3D model data are the original measurement data of the designed space
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