Machine Learning Research

Shape Clustering Using K-Medoids in Architectural Form Finding

Research Title: Shape Clustering Using K-Medoids in Architectural Form Finding Abstract: As the number of design candidates in generative systems is often high, there is a need for an articulation mechanism that assists designers in exploring the generated design set. This research aims to condense the solution set yet enhance heterogeneity in generative design systems.…

Keep reading

Machine Learning for an Articulated Design Space

Research Title: Application of an Automatic Shape Clustering Method into Generative and Design Optimization Systems Abstract: Despite their prevalence and extensive applications, generative and design optimization systems lack effective organizational methods of the excessive number of design options they produce, which is problematic for designers’ interaction. Ideally, a diverse and organized set of designs can…

Keep reading

Incorporating Form Diversity into Architectural Design Optimization

Research Title: Incorporating Form Diversity into Architectural Design Optimization Abstract: In this study, we introduce a new approach that incorporates form diversity into architectural design optimization, which will potentially accommodate designers’ aesthetic judgment into the whole building optimization process. Form diversity is defined here as the level of difference in building geometric forms. We developed…

Keep reading

%d bloggers like this: