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Juan Pineda-Jaramillo
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A review of Machine Learning (ML) algorithms used for modeling travel mode choice
J Pineda-Jaramillo
Dyna 86 (211), 32-41, 2019
692019
Modeling the energy consumption of trains by applying neural networks
J Pineda-Jaramillo, R Insa, P Martínez
Proceedings of the Institution of Mechanical Engineers, Part F: Journal of …, 2018
292018
Predicting the traction power of metropolitan railway lines using different machine learning models
J Pineda-Jaramillo, P Martínez-Fernández, I Villalba-Sanchis, ...
International Journal of Rail Transportation, 461-478, 2021
282021
Assessing the performance of gradient-boosting models for predicting the travel mode choice using household survey data
J Pineda-Jaramillo, Ó Arbeláez-Arenas
Journal of Urban Planning and Development 148 (2), 04022007, 2022
192022
Unveiling the relevance of traffic enforcement cameras on the severity of vehicle–pedestrian collisions in an urban environment with machine learning models
J Pineda-Jaramillo, H Barrera-Jiménez, R Mesa-Arango
Journal of Safety Research, 2022
162022
Travel time, trip frequency and motorised-vehicle ownership: A case study of travel behaviour of people with reduced mobility in Medellín
J Pineda-Jaramillo
Journal of Transport & Health 22, 101110, 2021
162021
A Shallow Neural Network approach for identifying the leading causes associated to pedestrian deaths in Medellín
J Pineda-Jaramillo
Journal of Transport & Health 19, 100912, 2020
152020
Missions and factors determining the demand for affordable mass space tourism in the United States: A machine learning approach
R Mesa-Arango, J Pineda-Jaramillo, D Araujo, J Bi, M Basva, F Viti
Acta Astronautica, 2023
112023
Identifying the rail operating features associated to intermodal freight rail operation delays
J Pineda-Jaramillo, F Viti
Transportation Research Part C: Emerging Technologies 147, 103993, 2023
102023
Modelling road traffic collisions using clustered zones based on Foursquare data in Medellín
J Pineda-Jaramillo, Ó Arbeláez-Arenas
Case Studies on Transport Policy 9 (2), 958-964, 2021
102021
Comparing energy consumption for rail transit routes through Symmetric Vertical Sinusoid Alignments (SVSA), and applying artificial neural networks. A case study of Metro …
J Pineda-Jaramillo, P Salvador-Zuriaga, R Insa-Franco
Dyna 84 (203), 17-23, 2017
102017
Railway and road discrete choice model for foreign trade freight between Antioquia and the Port of Cartagena
J Pineda-Jaramillo, I Sarmiento, J Córdoba
Ingeniería e Investigación 36 (3), 22-28, 2016
10*2016
Variables influyentes en la elección entre carretera y ferrocarril para carga general de comercio exterior
J Pineda-Jaramillo, I Sarmiento
Ingeniería solidaria 10 (17), 29-37, 2014
92014
Diagnóstico y evaluación de transporte de mercancías por ferrocarril en Colombia
J Pineda-Jaramillo
Ingeniería solidaria 12 (20), 151-161, 2016
72016
Short-term arrival delay time prediction in freight rail operations using data-driven models
J Pineda-Jaramillo, F Bigi, T Bosi, F Viti, A D’Ariano
IEEE Access, 2023
62023
Impact of symmetric vertical sinusoid alignments on infrastructure construction costs: optimizing energy consumption in metropolitan railway lines using artificial neural networks
J Pineda-Jaramillo, P Salvador-Zuriaga, P Martínez-Fernández, ...
Urban Rail Transit 6 (3), 145-156, 2020
62020
Analysing travel satisfaction of tourists towards a metro system from unstructured data
J Pineda-Jaramillo, D Pineda-Jaramillo
Research in Transportation Business & Management 100746, 2021
52021
Modelo de elección de modo de transporte entre carretera y ferrocarril para carga general susceptible a exportación-importación. Aplicación al corredor vial Medellín–puerto de …
J Pineda-Jaramillo
Universidad Nacional de Colombia, 2013
42013
Long-term fleet management for freight trains: assessing the impact of wagon maintenance through simulation of shunting policies
F Bigi, T Bosi, J Pineda-Jaramillo, F Viti, A D’Ariano
Journal of Rail Transport Planning & Management 29, 100430, 2024
32024
MLOps in freight rail operations
J Pineda-Jaramillo, F Viti
Engineering Applications of Artificial Intelligence 123, 106222, 2023
32023
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