Data Clustering in Urban Computational Modeling by Integrated Geometry and Imagery Features for Probabilistic Navigation

Data Clustering in Urban Computational Modeling by Integrated Geometry and Imagery Features for Probabilistic Navigation

Cities are considered complex and open environments with multidimensional aspects including urban forms, urban imagery, and urban energy performance. So, a platform that supports the dialogue between the user and the machine is crucial in urban computational modeling (UCM). In this paper, we present...

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Bibliographic Details
Main Authors: Chenyi Cai, Mohamed Zaghloul, Biao Li
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Applied Sciences
Subjects:
urban computational modeling
data clustering
feature extraction
IGIF
self-organizing map
probabilistic navigation
Online Access:https://www.mdpi.com/2076-3417/12/24/12704

Internet

https://www.mdpi.com/2076-3417/12/24/12704

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