| Home > Publications database > Automated Quality Assessment of Space-Continuous Models for Pedestrian Dynamics > print |
| 001 | 866252 | ||
| 005 | 20210628150953.0 | ||
| 024 | 7 | _ | |a 10.1007/978-3-030-11440-4_35 |2 doi |
| 024 | 7 | _ | |a 2128/23584 |2 Handle |
| 024 | 7 | _ | |a WOS:000653682700035 |2 WOS |
| 037 | _ | _ | |a FZJ-2019-05418 |
| 100 | 1 | _ | |a Kurtc, Valentina |b 0 |
| 111 | 2 | _ | |a Traffic and Granular Flow |g TGF17 |c Washington |d 2017-07-19 - 2017-07-22 |w USA |
| 245 | _ | _ | |a Automated Quality Assessment of Space-Continuous Models for Pedestrian Dynamics |
| 260 | _ | _ | |a Cham |c 2019 |b Springer International Publishing |
| 295 | 1 | 0 | |a Traffic and Granular Flow '17 / Hamdar, Samer H. (Editor) |
| 300 | _ | _ | |a 317-325 |
| 336 | 7 | _ | |a CONFERENCE_PAPER |2 ORCID |
| 336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
| 336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
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| 336 | 7 | _ | |a Contribution to a conference proceedings |b contrib |m contrib |0 PUB:(DE-HGF)8 |s 1575638633_31057 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a Contribution to a book |0 PUB:(DE-HGF)7 |2 PUB:(DE-HGF) |m contb |
| 520 | _ | _ | |a In this work we propose a methodology for assessment of pedestrian modelscontinuous in space.With respect to the Kolmogorov-Smirnov distance between twodata clouds, representing for instance simulated and the corresponding empiricaldata, we calculate an evaluation factor between zero and one. Based on the value ofthe herein developed factor, we make a statement about the goodness of the modelunder evaluation. Moreover this process can be repeated in an automatic way inorder to maximize the above mentioned factor and hence determine the optimal setof model parameters. |
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| 700 | 1 | _ | |a Chraibi, Mohcine |0 P:(DE-Juel1)132077 |b 1 |e Corresponding author |u fzj |
| 700 | 1 | _ | |a Tordeux, Antoine |0 P:(DE-HGF)0 |b 2 |
| 773 | _ | _ | |a 10.1007/978-3-030-11440-4_35 |
| 856 | 4 | _ | |y OpenAccess |u https://juser.fz-juelich.de/record/866252/files/author.pdf |
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| 914 | 1 | _ | |y 2019 |
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