Architectural space design methods using data algorithms - Jingyang Liu; Yifan Zhang; Shiru Zhao (AIP Advances)
Currently, various industries around the world are advocating innovation, and the design of architectural spaces is no exception. However, the innovation of traditional architectural space design methods is not enough. In view of the problems of the traditional architectural space design methods, such as weak quantification, weak logic, and low level of science and technology, this paper used the particle swarm optimization algorithm in the data algorithm to study the architectural space design methods. This paper introduced the principles of architectural space design, studied some existing design methods and problems, and used particle swarm optimization algorithm to make some innovations in architectural space design methods. Experts and scholars were invited to score to verify the superiority of particle swarm optimization algorithm for architectural space design. The residents’ satisfaction rate with the building space design method using particle swarm optimization algorithm was more than 91.65%, and the average satisfaction rate of 20 residents was 93.2%. At the same time, the space experts who used the particle swarm optimization algorithm to design the building space design method scored more than 8.34 points. Innovative design of architectural space requires methods. Only by applying the right approach can the ideal design effect be achieved as quickly as possible to ensure the quality of the design.