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dc.contributor.author | Wichmann S. | |
dc.contributor.author | Hammarström H. | |
dc.date.accessioned | 2021-02-25T20:35:06Z | |
dc.date.available | 2021-02-25T20:35:06Z | |
dc.date.issued | 2020 | |
dc.identifier.issn | 0378-4371 | |
dc.identifier.uri | https://dspace.kpfu.ru/xmlui/handle/net/161865 | |
dc.description.abstract | © 2019 Elsevier B.V. In many scientific disciplines it is often necessary to refer to geographical travel distances. While online services can provide such distances, they fail for larger distances or for distances between points not connected by roads, and they do not allow for the calculation of many distances. Here we describe two novel methods of measuring travel distances which overcome these problems. Both use waypoints of populated places from the geonames.org database. The more efficient and accurate of the two uses the Dijkstra algorithm to find the shortest path through a Delaunay graph of neighbouring populated places. | |
dc.relation.ispartofseries | Physica A: Statistical Mechanics and its Applications | |
dc.title | Methods for calculating walking distances | |
dc.type | Article | |
dc.relation.ispartofseries-volume | 540 | |
dc.collection | Публикации сотрудников КФУ | |
dc.source.id | SCOPUS03784371-2020-540-SID85073521902 |