TOPOLOGICAL DATA ANALYSIS:

LOCATING BETTI NUMBERS IN COMPLEX NETWORKS

CASE STUDY:
NYC SUBWAY SYSTEM

Convert complex network data, via the adjacency matrix to an abstract simplicial complex (asc). Compute the dimension and location of Betti numbers, i.e. homologies or higher dimensional holes, of the asc. 

This topological approach can yield novel insights distinct from traditional network analyses.

 

Actively working on processing subway system network and extracting insights via a systematic investigation of the topological resilience of the NYC subway system through a simulated percolation of stations and lines.

MORE INFORMATION AVAILABLE UPON REQUEST.

Link to Github - https://github.com/dgoldsmith93/BettiNumbers

 

New York, NY, USA

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©2017 by Daniel Goldsmith.