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- W2976410834 abstract "Two new methods of graph segment analysis are introduced and tested, which use a random walk as atheoretical and practical basis. The first, random walk betweenness (RWB), is a measure ofbetweenness centrality, similar to choice, and the second is a simple calculation of a random walk ona graph with similarities to visual agent simulation. To implement these, two methodologicalinnovations are made: angular weighting for probability of turns and a dual node representation ofsegments. The two methods are tested for their correlation with both pedestrian and vehicularmovement and compared with segment angular choice. RWB is seen not to be as effective aprediction of human movement, but simple random walks appear approximately as effective aschoice, and faster to compute. Practically, this yields a substantially faster algorithm for movementprediction than previously exists. Theoretically, it suggests a much simpler model of agency: thatnavigation may be more opportunistic than optimised. To the extent the latter is valid it may provevaluable to a more complete theory of movement and a bridge between Space Syntax and relatedfields of mathematical graph theory." @default.
- W2976410834 created "2019-10-03" @default.
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- W2976410834 date "2019-07-08" @default.
- W2976410834 modified "2023-09-26" @default.
- W2976410834 title "Random walks on weighted graphs: centrality measures or simple agents" @default.
- W2976410834 hasPublicationYear "2019" @default.
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