Exploring the Intersection of Biological and Artificial Neural Networks in Architectural Contexts, Followed by Investigation of Algorithms Supporting the Evolution of the Design Process

Abstract

This review explores the relationship between neural networks and architecture, specifically in the domains of facade design, interior design, and building construction. It investigates two types of neural networks: biological, representing the human brain’s neural system, and artificial, which are computational systems inspired by the brain’s structure and functions. The study provides a descriptive overview of these neural networks and their applications across various fields. It further examines how these networks integrate with architecture at different levels. The study emphasizes the concept of “neural architecture,” which combines artificial neural networks (ANNs) with architecture to generate multiple design possibilities and uncover hidden patterns. ANNs are utilized in creating smart buildings and optimizing structural design processes to reduce costs. Additionally, the study explores “neuroarchitecture,” which explores the interaction of biological neural networks (BNNs) with architecture, focusing on the impact of built environments on the brain and behavior. It combines principles from neuroscience, architecture, and environmental psychology. The analysis of case studies demonstrates the importance of AI tools such as ‘pix2pix’, GCNNs, DCGAN, CycleGAN, and StyleGAN in modernizing architectural design by blending traditional and contemporary styles and enhancing the creative process.