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Panchamy Krishnakumari
Panchamy Krishnakumari
Assistant Professor, TU Delft
Verifierad e-postadress på tudelft.nl
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Revealing the day-to-day regularity of urban congestion patterns with 3D speed maps
C Lopez, L Leclercq, P Krishnakumari, N Chiabaut, H Van Lint
Scientific Reports 7 (1), 14029, 2017
1092017
Feature extraction and clustering analysis of highway congestion
TT Nguyen, P Krishnakumari, SC Calvert, HL Vu, H Van Lint
Transportation Research Part C: Emerging Technologies 100, 238-258, 2019
862019
A data driven method for OD matrix estimation
P Krishnakumari, H Van Lint, T Djukic, O Cats
Transportation Research Part C: Emerging Technologies 113, 38-56, 2020
702020
Spatiotemporal partitioning of transportation network using travel time data
C Lopez, P Krishnakumari, L Leclercq, N Chiabaut, H Van Lint
Transportation Research Record 2623 (1), 98-107, 2017
652017
Metropolitan rail network robustness
O Cats, P Krishnakumari
Physica A: statistical mechanics and its applications 549, 124317, 2020
502020
A data driven method for OD matrix estimation
P Krishnakumari, H van Lint, T Djukic, O Cats
Transportation Research Procedia 38, 139-159, 2019
372019
Exploring demand patterns of a ride-sourcing service using spatial and temporal clustering
TLK Liu, P Krishnakumari, O Cats
2019 6th international conference on models and technologies for intelligent …, 2019
172019
Traffic congestion pattern classification using multi-class SVM
HN Nguyen, P Krishnakumari, HL Vu, H van Lint
2016 IEEE 19th International Conference on Intelligent Transportation …, 2016
172016
Understanding network traffic states using transfer learning
P Krishnakumari, A Perotti, V Pinto, O Cats, H van Lint
2018 21st International Conference on Intelligent Transportation Systems …, 2018
152018
Traffic congestion pattern classification using multiclass active shape models
P Krishnakumari, T Nguyen, L Heydenrijk-Ottens, HL Vu, H van Lint
Transportation Research Record 2645 (1), 94-103, 2017
152017
Virus spreading in public transport networks: the alarming consequences of the business as usual scenario
P Krishnakumari, O Cats
TU Delft, 2020
132020
Estimation of metro network passenger delay from individual trajectories
P Krishnakumari, O Cats, H van Lint
Transportation Research Part C: Emerging Technologies 117, 102704, 2020
112020
Effectiveness of trip planner data in predicting short-term bus ridership
Z Wang, AJ Pel, T Verma, P Krishnakumari, P van Brakel, N van Oort
Transportation Research Part C: Emerging Technologies 142, 103790, 2022
72022
Virus Spreading in Public Transport Networks
P Krishnakumari, O Cats
Working paper. Transport Institute TU Delft, 2020
72020
Supervised learning for measuring hip joint distance in digital X-ray images
PK Krishnakumari
62015
Rail network robustness: The role of rapid development and a polycentric structure in withstanding random and targeted attacks
O Cats, P Krishnakumari, K Tundulyasaree
Proceedings of the Transportation Research Board 98th Annual Meeting …, 2019
42019
Invloed van COVID-19 op verkeersafwikkeling
SP Hoogendoorn, W Daamen, Y Yuan, PK Krishnakumari
Tijdschrift Vervoerswetenschap 57 (1), 41-69, 2021
32021
Heuristic Coarsening for Generating Multiscale Transport Networks
P Krishnakumari, O Cats, H van Lint
IEEE Transactions on Intelligent Transportation Systems 21 (6), 2240-2253, 2019
32019
Understanding physical distancing compliance behaviour using proximity and survey data: A case study in the Netherlands during the COVID-19 pandemic
L Van Schaik, D Duives, S Hoogendoorn-Lanser, JW Hoekstra, ...
Transportation Research Procedia 76, 505-519, 2024
22024
Improving the service of E-bike sharing by demand pattern analysis: A data-driven approach
Z Zhang, P Krishnakumari, F Schulte, N van Oort
Research in Transportation Economics 101, 101340, 2023
22023
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Artiklar 1–20