SwePub
Sök i SwePub databas

  Extended search

Träfflista för sökning "WFRF:(Borgelt C.) "

Search: WFRF:(Borgelt C.)

  • Result 1-3 of 3
Sort/group result
   
EnumerationReferenceCoverFind
1.
  • Di Fatta, G., et al. (author)
  • Preface
  • 2011
  • In: IEEE International Conference on Data Mining. Proceedings. - : Institute of Electrical and Electronics Engineers (IEEE). - 1550-4786. ; , s. xlviii-xlvix
  • Journal article (peer-reviewed)
  •  
2.
  • Grantson Borgelt, Magdalene, et al. (author)
  • Minimum weight triangulation by cutting out triangles
  • 2005
  • In: Algorithms and computation / Lecture notes in computer science. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 0302-9743 .- 1611-3349. - 9783540309352 ; 3827, s. 984-994
  • Conference paper (peer-reviewed)abstract
    • We describe a fixed parameter algorithm for computing the minimum weight triangulation (MWT) of a simple polygon with (n - k) vertices on the perimeter and k hole vertices in the interior, that is, for a total of n vertices. Our algorithm is based on cutting out empty triangles (that is, triangles not containing any holes) from the polygon and processing the parts or the rest of the polygon recursively. We show that with our algorithm a minimum weight triangulation can be found in time at most O(n(3)k! k), and thus in O(n(3)) if k is constant. We also note that k! can actually be replaced by b(k) for some constant b. We implemented our algorithm in Java and report experiments backing our analysis.
  •  
3.
  • Bachmann, A., et al. (author)
  • Incremental frequent route based trajectory prediction
  • 2013
  • In: IWCTS 2013 - 6th ACM SIGSPATIAL International Workshop on Computational Transportation Science. - New York, NY, USA : Association for Computing Machinery (ACM). - 9781450325271 ; , s. 49-54
  • Conference paper (peer-reviewed)abstract
    • Recent technological trends enable modern traffic prediction and management systems in which the analysis and prediction of movements of objects is essential. To this extent the present paper proposes IncCCFR - a novel, incremental approach for managing, mining, and predicting the incrementally evolving trajectories of moving objects. In addition to reduced mining and storage costs, a key advantage of the incremental approach is its ability to combine multiple temporally relevant mining results from the past to capture temporal and periodic regularities in movement. The approach and its variants are empirically evaluated on a large real-world data set of moving object trajectories, originating from a fleet of taxis, illustrating that detailed closed frequent routes can be efficiently discovered and used for prediction.
  •  
Skapa referenser, mejla, bekava och länka
  • Result 1-3 of 3

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Close

Copy and save the link in order to return to this view