Building layout generation has entered a new era in recent years, leveraging state-of-the-art
deep generative methods to learn morphological properties of exiting urban structures and …

Abstract Generative Adversarial Network (GAN) is widely used in many generative
problems, including in spatial information sciences and urban systems. The data generated …

Participatory urban planning is the mainstream of modern urban planning that involves the
active engagement of residents. However, the traditional participatory paradigm requires …

Integrating deep generative models into urban form generation is an innovative and
promising approach to support the urban design process. However, most deep generative …

Scenario planning is a powerful tool for cities to navigate uncertainties and mitigate the
impacts of adverse scenarios by projecting future outcomes based on present-day …

In the rapidly evolving landscape of technology, the emergence of Chat Generative Pre-
trained Transformer (ChatGPT) marks a pivotal milestone in the realm of Artificial …

Automated site planning, powered by deep generative methods, excels in creating solutions
responsive to exiting city structures but often overlooks user-specific design scenarios …

Abstract The application of Artificial Intelligence (AI) is a popular trend to make damage
inspection and analysis in structural health monitoring more intelligent and automatic …

The utilization of deep learning for form analysis facilitates the classification of an extensive
number of forms based on their morphological features. A critical consideration for …

The morphological design of urban space affects the quality of the environment. The
traditional experience-based design approach was greatly improved by introducing …