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Ulrich Weidmann 0001

Ulrich Alois Weidmann

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affiliation: ETH Zurich, Institute for Transport Planning and Systems (IVT), Switzerland

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2020 – today

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2021
[j9]
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Pier Giuseppe Sessa, Valerio De Martinis, Axel Bomhauer-Beins, Ulrich Alois Weidmann, Francesco Corman:
A hybrid stochastic approach for offline train trajectory reconstruction. Public Transp. 13(3): 675-698 (2021)
2020
[j8]
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Ambra Toletti, Marco Laumanns, Ulrich Weidmann:
Coordinated railway traffic rescheduling with the Resource Conflict Graph model. J. Rail Transp. Plan. Manag. 15: 100173 (2020)

2010 – 2019

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2018
[j7]
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Sabrina Herrigel, Marco Laumanns, Jácint Szabó, Ulrich Weidmann:
Periodic railway timetabling with sequential decomposition in the PESP model. J. Rail Transp. Plan. Manag. 8(Issues): 167-183 (2018)
2016
[c1]
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Ambra Toletti, Valerio De Martinis, Ulrich Weidmann:
Energy savings in mixed rail traffic rescheduling: an RCG approach. ITSC 2016: 2430-2435
2015
[j6]
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Olga Fink, Enrico Zio, Ulrich Weidmann:
Fuzzy Classification With Restricted Boltzman Machines and Echo-State Networks for Predicting Potential Railway Door System Failures. IEEE Trans. Reliab. 64(3): 861-868 (2015)
[j5]
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Olga Fink, Enrico Zio, Ulrich Weidmann:
A Classification Framework for Predicting Components' Remaining Useful Life Based on Discrete-Event Diagnostic Data. IEEE Trans. Reliab. 64(3): 1049-1056 (2015)
2014
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Olga Fink, Enrico Zio, Ulrich Weidmann:
Quantifying the reliability of fault classifiers. Inf. Sci. 266: 65-74 (2014)
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Olga Fink, Enrico Zio, Ulrich Weidmann:
Predicting component reliability and level of degradation with complex-valued neural networks. Reliab. Eng. Syst. Saf. 121: 198-206 (2014)
2013
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Olga Fink, Enrico Zio, Ulrich Weidmann:
Predicting time series of railway speed restrictions with time-dependent machine learning techniques. Expert Syst. Appl. 40(15): 6033-6040 (2013)
2011
[j1]
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Bernhard Alt, Ulrich Weidmann:
A stochastic multiple area approach for public transport network design. Public Transp. 3(1): 65 (2011)

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