Enviaments recents

Autonomous counter-drone: is reinforcement learning the solution ?

Barrado Muxí, Cristina (2022)
Text en actes de congrés
Accés obert

Unmanned aircraft are becoming available to most purchasers due to their decreasing costs and increasing functionalities. While this fact opens the opportunity to new business and services, it also represents a potential ...

Explainability of deep reinforcement learning method with drones

Çetin, Ender; Barrado Muxí, Cristina; Pastor Llorens, Enric (2023)
Text en actes de congrés
Accés obert

Recent advances in artificial intelligence (AI) technology demonstrated that AI algorithms are very powerful as AI models become more complex. As a result, the users and also the engineers who developed the AI algorithms ...

Generation of RNP approach flight procedures with an RRT* path-planning algorithm

Sáez García, Raúl; Toratani, Daichi; Mori, Ryota; Prats Menéndez, Xavier (2023)
Text en actes de congrés
Accés obert

We present a framework capable of generating required navigation performance authorization required approach (RNP AR APCH) procedures by using a combination of the optimal version of the path-planning rapidly-exploring ...

An enriched finite elements approach for multi-phase microsystems

Narváez Muñoz, Christian; Hashemi, Mohammad Reza; Ryzhakov, Pavel; Pons Prats, Jordi; Martí, Julio Marcelo (2023)
Text en actes de congrés
Accés restringit per política de l'editorial

This study presents an E-FEM/L-S approach for modeling fluid-fluid inter-face deformation in microsystems under electric fields. The approach treats the interface as a zero-thickness boundary and precisely models discontinuities ...

Would airspace users accept potential delays or reroutings for a discount in route charges? Results of a stated preferences survey

Melgosa Farrés, Marc; Kuljanin, Jovana; Jovanovic, Radosav; Fichert, Frank (2022)
Text en actes de congrés
Accés obert

Pre-tactical prediction of atfm delay for individual flights

Mas Pujol, Sergi; De Falco, Paolino; Salamí San Juan, Esther; Delgado Muñoz, Luis (Institute of Electrical and Electronics Engineers (IEEE), 2022)
Text en actes de congrés
Accés obert

Airlines develop an operation plan, during the day prior to operations (D-1), to identify potential network issues and prepare potential pre-tactical preventing measures such as aircraft tail swapping or crew reassignment ...

Dispatcher3 – Machine learning for efficient flight planning: approach and challenges for data-driven prototypes in air transport

Delgado Muñoz, Luis; Mas Pujol, Sergi; Skorobogatov, Georgy; Argerich, Clara; Gregori, Ernesto (2022)
Text en actes de congrés
Accés obert

Machine learning techniques to support decisionmaking processes are in trend. These are particularly relevant in the context of flight management where large datasets of planned and realised operations are available. ...

UPCommons. Portal del coneixement obert de la UPC

Ponències/Comunicacions de congressos: Enviaments recents

Autonomous counter-drone: is reinforcement learning the solution ?

Explainability of deep reinforcement learning method with drones

Generation of RNP approach flight procedures with an RRT* path-planning algorithm

An enriched finite elements approach for multi-phase microsystems

Would airspace users accept potential delays or reroutings for a discount in route charges? Results of a stated preferences survey

Pre-tactical prediction of atfm delay for individual flights

Dispatcher3 – Machine learning for efficient flight planning: approach and challenges for data-driven prototypes in air transport

Effects of capacity sharing on delays and re-routings in European ATM

Data-driven estimation of flights’ hidden parameters

In-flight cost index optimisation upon weather forecast updates

Alternative 4D trajectories for the avoidance of weather- and contrail-sensitive volumes

Considering TMA holding uncertainty into in-flight trajectory optimisation

Explora

Ponències/Comunicacions de congressos: Enviaments recents

Autonomous counter-drone: is reinforcement learning the solution ? ﻿

Explainability of deep reinforcement learning method with drones ﻿

Generation of RNP approach flight procedures with an RRT* path-planning algorithm ﻿

An enriched finite elements approach for multi-phase microsystems ﻿

Would airspace users accept potential delays or reroutings for a discount in route charges? Results of a stated preferences survey ﻿

Pre-tactical prediction of atfm delay for individual flights ﻿

Dispatcher3 – Machine learning for efficient flight planning: approach and challenges for data-driven prototypes in air transport ﻿

Effects of capacity sharing on delays and re-routings in European ATM ﻿

Data-driven estimation of flights’ hidden parameters ﻿

In-flight cost index optimisation upon weather forecast updates ﻿

Alternative 4D trajectories for the avoidance of weather- and contrail-sensitive volumes ﻿

Considering TMA holding uncertainty into in-flight trajectory optimisation ﻿

Autonomous counter-drone: is reinforcement learning the solution ?

Explainability of deep reinforcement learning method with drones

Generation of RNP approach flight procedures with an RRT* path-planning algorithm

An enriched finite elements approach for multi-phase microsystems

Would airspace users accept potential delays or reroutings for a discount in route charges? Results of a stated preferences survey

Pre-tactical prediction of atfm delay for individual flights

Dispatcher3 – Machine learning for efficient flight planning: approach and challenges for data-driven prototypes in air transport

Effects of capacity sharing on delays and re-routings in European ATM

Data-driven estimation of flights’ hidden parameters

In-flight cost index optimisation upon weather forecast updates

Alternative 4D trajectories for the avoidance of weather- and contrail-sensitive volumes

Considering TMA holding uncertainty into in-flight trajectory optimisation