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Found 6 papers, 0 papers with code
Online Relocating and Matching of Ride-Hailing Services: A Model-Based Modular Approach
This study proposes an innovative model-based modular approach (MMA) to dynamically optimize order matching and vehicle relocation in a ride-hailing platform.
Vehicle Dispatching and Routing of On-Demand Intercity Ride-Pooling Services: A Multi-Agent Hierarchical Reinforcement Learning Approach
The integrated development of city clusters has given rise to an increasing demand for intercity travel.
Data-driven Method for Estimating Aircraft Mass from Quick Access Recorder using Aircraft Dynamics and Multilayer Perceptron Neural Network
This paper presents a data-driven method involving use of the quick access recorder (QAR)-a digital flight-data recorder-installed on all aircrafts to record the initial aircraft climb mass during each flight.
Multi-Vehicle Routing Problems with Soft Time Windows: A Multi-Agent Reinforcement Learning Approach
Multi-vehicle routing problem with soft time windows (MVRPSTW) is an indispensable constituent in urban logistics distribution systems.
Computational Efficiency
Multi-agent Reinforcement Learning
+2
Feature Learning Viewpoint of AdaBoost and a New Algorithm
We explain the rationality of this and illustrate the theorem that when the dimension of these features increases, the performance of SVM would not be worse, which can explain the resistant to overfitting of AdaBoost.
Multistep Speed Prediction on Traffic Networks: A Graph Convolutional Sequence-to-Sequence Learning Approach with Attention Mechanism
Multistep traffic forecasting on road networks is a crucial task in successful intelligent transportation system applications.
