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Guido Cantelmo
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2020 – today
- 2023
- [j5]Giovanni Ceccarelli, Guido Cantelmo, Marialisa Nigro
, Constantinos Antoniou
Learning from Imbalanced Datasets: The Bike-Sharing Inventory Problem Using Sparse Information. Algorithms 16(7): 351 (2023) - [j4]Natalia Selini Hadjidimitriou
Machine learning for activity pattern detection. J. Intell. Transp. Syst. 27(6): 834-848 (2023) - [c15]Mirfarnam Tabandeh, Constantinos Antoniou, Guido Cantelmo:
Long-term & short-term bike sharing demand predictions using contextual data. MT-ITS 2023: 1-6 - 2022
- [j3]Sérgio F. A. Batista, Guido Cantelmo, Mónica Menéndez, Constantinos Antoniou:
A Gaussian sampling heuristic estimation model for developing synthetic trip sets. Comput. Aided Civ. Infrastructure Eng. 37(1): 93-109 (2022) - [j2]Piergiorgio Vitello
Mobility-Driven and Energy-Efficient Deployment of Edge Data Centers in Urban Environments. IEEE Trans. Sustain. Comput. 7(4): 736-748 (2022) - 2021
- [c14]Giovanni Ceccarelli, Guido Cantelmo, Marialisa Nigro, Constantinos Antoniou:
Machine Learning from imbalanced data-sets: an application to the bike-sharing inventory problem. MT-ITS 2021: 1-6
2010 – 2019
- 2019
- [c13]Piergiorgio Vitello, Andrea Capponi
The Impact of Human Mobility on Edge Data Center Deployment in Urban Environments. GLOBECOM 2019: 1-6 - [c12]Andrea Capponi
Crowdsensed Data Learning-Driven Prediction of Local Businesses Attractiveness in Smart Cities. ISCC 2019: 1-6 - [c11]Guido Cantelmo, Rafal Kucharski
A low dimensional model for bike sharing demand forecasting. MT-ITS 2019: 1-7 - [c10]Filippo Carrese, Guido Cantelmo
Leveraging GIS Data and Topological Information to Infer Trip Chaining Behaviour at Macroscopic Level. MT-ITS 2019: 1-10 - [i1]Guido Cantelmo, Moeid Qurashi, A. Arun Prakash, Constantinos Antoniou, Francesco Viti:
Incorporating Trip Chaining within Online Demand Estimation. CoRR abs/1910.00400 (2019) - 2018
- [c9]Bogdan Toader, Guido Cantelmo
Using Passive Data Collection Methods to Learn Complex Mobility Patterns: An Exploratory Analysis. ITSC 2018: 993-998 - 2017
- [c8]Guido Cantelmo
Effectiveness of the two-step dynamic demand estimation model on large networks. MT-ITS 2017: 356-361 - [c7]Sébastien Faye, Guido Cantelmo
Demo: MAMBA: A platform for personalised multimodal trip planning. VNC 2017: 117-118 - 2016
- [c6]Guido Cantelmo
A network-wide assessment of local signal control policies' performance in practical implementations. ITSC 2016: 939-944 - 2015
- [c5]Guido Cantelmo
A Two-Steps Dynamic Demand Estimation Approach Sequentially Adjusting Generations and Distributions. ITSC 2015: 1477-1482 - [c4]Ernesto Cipriani
The Impact of Route Choice Modeling on Dynamic OD Estimation. ITSC 2015: 1483-1488 - [c3]Guido Cantelmo
Systematic assessment of local & global signal control policies: A methodological perspective. MT-ITS 2015: 156-163 - [c2]Selini Natalia Hadjidimitriou
Assessing the consistency between observed and modelled route choices through GPS data. MT-ITS 2015: 216-222 - [c1]Simone Aniello Di Donna, Guido Cantelmo
A Markov chain dynamic model for trip generation and distribution based on CDR. MT-ITS 2015: 243-250 - 2014
- [j1]Guido Cantelmo
An Adaptive Bi-Level Gradient Procedure for the Estimation of Dynamic Traffic Demand. IEEE Trans. Intell. Transp. Syst. 15(3): 1348-1361 (2014)
Coauthor Index
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