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dc.contributor.advisorHaddow, Paulinenb_NO
dc.contributor.authorEilertsen, Bjørn Gunnarnb_NO
dc.date.accessioned2014-12-19T13:40:55Z
dc.date.available2014-12-19T13:40:55Z
dc.date.created2013-11-08nb_NO
dc.date.issued2013nb_NO
dc.identifier663032nb_NO
dc.identifierntnudaim:8554nb_NO
dc.identifier.urihttp://hdl.handle.net/11250/253548
dc.description.abstractThis thesis is a research in computer science and artificial intelligence, more precisely a research in biologically inspired methods. Procedural techniques, inspired by biological developmental models, are known to create complex structures from compact descriptions. This motivates exploring procedural techniques on the subject of automatically generating 3D road network models. In this thesis are L-systems applied to procedurally develop vast road networks, and genetic algorithms (GAs) are applied to tune the procedure to target outcomes. The final solution also incorporates a maximum flow algorithm combined with a genetic algorithm to tune intersections in the road network.nb_NO
dc.languageengnb_NO
dc.publisherInstitutt for datateknikk og informasjonsvitenskapnb_NO
dc.titleAutomatic road network generation with L-systems and genetic algorithmsnb_NO
dc.typeMaster thesisnb_NO
dc.source.pagenumber63nb_NO
dc.contributor.departmentNorges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikk, Institutt for datateknikk og informasjonsvitenskapnb_NO


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