Research on Machine Learning Methods That Promote Public Participation in Urban Design
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DOI: 10.23977/icmit2021.004
Corresponding Author
Jin Shang
ABSTRACT
Public participation promotes innovative ways to increase the efficiency of urban design and planning (Amado et al., 2010) but it also presents many challenges to be effective. This paper introduces the current situation of public participation and how current machine learning (ML) tools can support it. Then we propose new methods based on machine learning to improve the communication between urban designers and participants. Finally, we discuss potential effects of this new method on public participation.
KEYWORDS
Public Participation, Urban Design, Machine Learning