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Found 5 papers, 3 papers with code
Noise-Aware and Equitable Urban Air Traffic Management: An Optimization Approach
Urban air mobility (UAM), a transformative concept for the transport of passengers and cargo, faces several integration challenges in complex urban environments.
Class Binarization to NeuroEvolution for Multiclass Classification
In this paper, we apply class binarization techniques to a neuroevolution algorithm, NeuroEvolution of Augmenting Topologies (NEAT), that is used to generate neural networks for multiclass classification.
Improved Aircraft Environmental Impact Segmentation via Metric Learning
Accurate modeling of aircraft environmental impact is pivotal to the design of operational procedures and policies to mitigate negative aviation environmental impact.
Risk-aware Urban Air Mobility Network Design with Overflow Redundancy
In our methodology, we first model how disruptions to a given UAM network might impact on the nominal traffic flow and how this flow might be re-accommodated on an extended network with reserve capacity.
A Framework for Learning Predator-prey Agents from Simulation to Real World
In such a framework, users only need to focus on algorithms without being worried about the detail of manipulating robots in both simulation and the real world.
