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From Data to Actions in Intelligent Transportation Systems: a
  Prescription of Functional Requirements for Model Actionability

From Data to Actions in Intelligent Transportation Systems: a Prescription of Functional Requirements for Model Actionability

6 February 2020
I. Laña
J. S. Medina
E. Vlahogianni
Javier Del Ser
ArXivPDFHTML

Papers citing "From Data to Actions in Intelligent Transportation Systems: a Prescription of Functional Requirements for Model Actionability"

10 / 10 papers shown
Title
A Catalog of Fairness-Aware Practices in Machine Learning Engineering
A Catalog of Fairness-Aware Practices in Machine Learning Engineering
Gianmario Voria
Giulia Sellitto
Carmine Ferrara
Francesco Abate
A. Lucia
F. Ferrucci
Gemma Catolino
Fabio Palomba
FaML
29
3
0
29 Aug 2024
State-of-the-Art Review: The Use of Digital Twins to Support Artificial
  Intelligence-Guided Predictive Maintenance
State-of-the-Art Review: The Use of Digital Twins to Support Artificial Intelligence-Guided Predictive Maintenance
Sizhe Ma
Katherine A. Flanigan
Mario Bergés
26
4
0
19 Jun 2024
State-of-the-Art Review and Synthesis: A Requirement-based Roadmap for
  Standardized Predictive Maintenance Automation Using Digital Twin
  Technologies
State-of-the-Art Review and Synthesis: A Requirement-based Roadmap for Standardized Predictive Maintenance Automation Using Digital Twin Technologies
Sizhe Ma
Katherine A. Flanigan
Mario Bergés
16
8
0
13 Nov 2023
Traffic Prediction using Artificial Intelligence: Review of Recent
  Advances and Emerging Opportunities
Traffic Prediction using Artificial Intelligence: Review of Recent Advances and Emerging Opportunities
Maryam Shaygan
Collin Meese
Wanxin Li
Xiaoliang (George) Zhao
Mark M. Nejad
22
108
0
31 May 2023
Adaptive Modeling of Uncertainties for Traffic Forecasting
Adaptive Modeling of Uncertainties for Traffic Forecasting
Ying Wu
Yongchao Ye
Adnan Zeb
James J. Q. Yu
Z. Wang
AI4TS
24
7
0
16 Mar 2023
Measuring the Confidence of Traffic Forecasting Models: Techniques,
  Experimental Comparison and Guidelines towards Their Actionability
Measuring the Confidence of Traffic Forecasting Models: Techniques, Experimental Comparison and Guidelines towards Their Actionability
I. Laña
Ignacio
I. Olabarrieta
Javier Del Ser
32
1
0
28 Oct 2022
Vision Paper: Causal Inference for Interpretable and Robust Machine
  Learning in Mobility Analysis
Vision Paper: Causal Inference for Interpretable and Robust Machine Learning in Mobility Analysis
Yanan Xin
Natasa Tagasovska
F. Pérez-Cruz
Martin Raubal
27
10
0
18 Oct 2022
A Graph-based Methodology for the Sensorless Estimation of Road Traffic
  Profiles
A Graph-based Methodology for the Sensorless Estimation of Road Traffic Profiles
Eric L. Manibardo
I. Laña
Esther Villar-Rodriguez
Javier Del Ser
22
3
0
11 Jan 2022
Deep Learning for Road Traffic Forecasting: Does it Make a Difference?
Deep Learning for Road Traffic Forecasting: Does it Make a Difference?
Eric L. Manibardo
I. Laña
Javier Del Ser
AI4TS
24
67
0
02 Dec 2020
Deep Echo State Networks for Short-Term Traffic Forecasting: Performance
  Comparison and Statistical Assessment
Deep Echo State Networks for Short-Term Traffic Forecasting: Performance Comparison and Statistical Assessment
Javier Del Ser
I. Laña
Eric L. Manibardo
I. Oregi
E. Osaba
J. Lobo
Miren Nekane Bilbao
E. Vlahogianni
20
16
0
17 Apr 2020
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