Characterisation of collective motion

dc.contributor.authorKjellman, Cecilia
dc.contributor.departmentChalmers tekniska högskola / Institutionen för energi och miljösv
dc.contributor.departmentChalmers University of Technology / Department of Energy and Environmenten
dc.date.accessioned2019-07-03T13:51:37Z
dc.date.available2019-07-03T13:51:37Z
dc.date.issued2015
dc.description.abstractSelf-organisation and emergence is a widespread and fundamental aspect of biological systems. Fish schools, insect swarms, bird ocks, colonies of bac- teria and human crowds are familiar examples of systems of very different levels of complexity and scale. To determine what governs interaction in the many biological systems is of importance. This thesis mainly focuses on comparing information usage for modelling collective motion, comparing using the distance to neighbouring individuals and time to collision. The thesis begins with analysing gathered sh school data in light of recent work in the eld of human crowd behaviour. The method uses a pair distribution function and a possible interaction energy to compare the two characteristics distance to neighbouring individuals and time to collision. The result differs in an interesting way from the original article on human crowd behaviour. The later part of the thesis describes existing collective behaviour models, and model adjustments, using either distance or time to collision as the most important attribute. Suitable existing measurements are touched upon. Fi- nally simulations using the included models are discussed but no conclusion regarding any decisive variable is made.
dc.identifier.urihttps://hdl.handle.net/20.500.12380/226388
dc.language.isoeng
dc.relation.ispartofseriesRapportserie för Avdelningen för fysisk resursteori : 2015:23
dc.setspec.uppsokLifeEarthScience
dc.subjectAnnan naturvetenskap
dc.subjectEnergi
dc.subjectOther Natural Sciences
dc.subjectEnergy
dc.titleCharacterisation of collective motion
dc.type.degreeExamensarbete för masterexamensv
dc.type.degreeMaster Thesisen
dc.type.uppsokH
local.programmeComplex adaptive systems (MPCAS), MSc
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