Zobrazeno 1 - 10
of 234
pro vyhledávání: '"Michael Behrisch"'
Publikováno v:
SUMO Conference Proceedings, Vol 5 (2024)
This paper examined the performances of the current four battery models in SUMO. The possibility of expanding the model parameterization was also investigated and the corresponding extension was carried out for PHEMlight. Accordingly, the models can
Externí odkaz:
https://doaj.org/article/91bfc2ebd7754ce3bb9e8dcf8e375b83
Autor:
Aboozar Roosta, Heather Kaths, Mirko Barthauer, Jakob Erdmann, Yun-Pang Flötteröd, Michael Behrisch
Publikováno v:
SUMO Conference Proceedings, Vol 4 (2023)
Microscopic traffic simulation tools provide ever-increasing value in the design and implementation of motor vehicle transport systems. Research and development of automated and intelligent technologies have highlighted the usefulness of simulation t
Externí odkaz:
https://doaj.org/article/9e0bbc9e2af548b5b03e2c25feee1ec9
Autor:
Michael Behrisch, Pauline Hartwig
Publikováno v:
SUMO Conference Proceedings, Vol 2 (2022)
There are already several tools available to generate traffic demand for the microscopic simulation suite SUMO. This paper focuses on setting up a simulation scenario for the peak hour in a small conurbation when there are vehicle counts available fo
Externí odkaz:
https://doaj.org/article/057902ed32c04c709b9374df7a685268
Autor:
Yun-Pang Flötteröd, Michael Behrisch
Publikováno v:
SUMO Conference Proceedings, Vol 2 (2022)
Currently, the city of Huainan, China, is constructing its intelligent transportation system, and traffic and environmental monitoring system for efficiently and effectively monitoring and managing city traffic. DLR’s traffic information platform K
Externí odkaz:
https://doaj.org/article/a44d5ab6e3ac44d09f278dac8ce41e50
Autor:
Alexandru Telea, Michael Behrisch
Publikováno v:
Data Science for Migration and Mobility ISBN: 9780197267103
Several visualisation methods have been recently proposed to aid a wide variety of users in the exploration of geographical trajectory, or trail, datasets. Such datasets consist of thousands up to millions of spatio-temporal trails that are also attr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::94ca6752608278aed99340cf39a66e3b
https://doi.org/10.5871/bacad/9780197267103.003.0011
https://doi.org/10.5871/bacad/9780197267103.003.0011
Publikováno v:
IEEE transactions on visualization and computer graphics.
We present PSEUDo, a visual pattern retrieval tool for multivariate time series. It aims to overcome the uneconomic (re-)training problem accompanying deep learning-based methods. Very high-dimensional time series emerge on an unprecedented scale due
Publikováno v:
SSRN Electronic Journal.
Autor:
Hanspeter Pfister, Hendrik Strobelt, Michael Behrisch, Alexander M. Rush, Sebastian Gehrmann, Adam Perer
Publikováno v:
IEEE Transactions on Visualization and Computer Graphics. 25:353-363
Neural Sequence-to-Sequence models have proven to be accurate and robust for many sequence prediction tasks, and have become the standard approach for automatic translation of text. The models work in a five stage blackbox process that involves encod
Autor:
Matthias Heinrichs, Thorsten Neumann, Jakob Erdmann, Anke Sauerländer-Biebl, Michael Behrisch
Publikováno v:
Transportation Research Procedia. 41:295-308
Urban mobility is changing and needs to change in order to meet future social requirements in terms of efficient and comfortable transport as well as reduced air pollution and noise. Moreover, climate change leads to an urgent need of reducing the CO
Autor:
Ryan Bartelme, Michael Behrisch, Emily Jean Cain, Remco Chang, Ishita Debnath, Bryan Heidorn, Pankaj Jaiswal, David Shaner LeBauer, null Mosca, Monica Munoz-Torres, Arun Ross, Kent Shefchek, Tyson L Swetnam, Anne E. Thessen
The interplay between an organism's genes, its environment, and the expressed phenotype is dynamic. These interactions within ecosystems are shaped by non-linear multi-scale effects that are difficult to disentangle into discrete components. In the f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2e58d3a9524cedfd340082da29a51345
https://doi.org/10.31219/osf.io/yx7t9
https://doi.org/10.31219/osf.io/yx7t9