As artificial intelligence (AI) technologies continually evolve, they penetrate multiple industries and extend a variety of applications such as image discrimination, voice assistant and smart translator etc. Inspired by the trend of AI, this paper reflected on the traditional design approaches in urban and architecture field, and tried to address the essential problems in the existing ways by combining pioneer design approaches (associative design, algorithmic design) and machine learning, deep learning methods. Taking the feasibility and limitations of the associative design and algorithmic design into account, an artificial intelligence design approach was explored and demonstrated with corresponding practical cases. Based on outcomes of research and practice, this paper further discussed the possibility and application scenarios of AI design in the future.
CITATION STYLE
Zheng, H. (2020). Form Finding and Evaluating Through Machine Learning: The Prediction of Personal Design Preference in Polyhedral Structures. In Architectural Intelligence (pp. 207–217). Springer Nature Singapore. https://doi.org/10.1007/978-981-15-6568-7_13
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