Multidimensional urban segregation: toward a neural network measure

@article{Olteanu2019MultidimensionalUS,
  title={Multidimensional urban segregation: toward a neural network measure},
  author={Madalina Olteanu and Aur{\'e}lien Hazan and Marie Cottrell and Julien Randon-Furling},
  journal={Neural Computing and Applications},
  year={2019},
  pages={1-13}
}
We introduce a multidimensional, neural network approach to reveal and measure urban segregation phenomena, based on the self-organizing map algorithm (SOM). The multidimensionality of SOM allows one to apprehend a large number of variables simultaneously, defined on census blocks or other types of statistical blocks, and to perform clustering along them. Levels of segregation are then measured through correlations between distances on the neural network and distances on the actual geographical… 
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