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Found 6 papers, 2 papers with code
Towards a connection between the capacitated vehicle routing problem and the constrained centroid-based clustering
At the first step, a constrained centroid-based clustering algorithm generates feasible clusters of customers.
Rule-Extraction Methods From Feedforward Neural Networks: A Systematic Literature Review
Motivated by the interpretability question in ML models as a crucial element for the successful deployment of AI systems, this paper focuses on rule extraction as a means for neural networks interpretability.
Improving day-ahead Solar Irradiance Time Series Forecasting by Leveraging Spatio-Temporal Context
Solar power harbors immense potential in mitigating climate change by substantially reducing CO$_{2}$ emissions.
MAgNet: Mesh Agnostic Neural PDE Solver
The computational complexity of classical numerical methods for solving Partial Differential Equations (PDE) scales significantly as the resolution increases.
Neural Combinatorial Optimization with Reinforcement Learning : Solving theVehicle Routing Problem with Time Windows
In contrast to the classical techniques for solving combinatorial optimization problems, recent advancements in reinforcement learning yield the potential to independently learn heuristics without any human interventions.
Machine Learning Approaches for Traffic Volume Forecasting: A Case Study of the Moroccan Highway Network
In this paper, we aim to illustrate different approaches we followed while developing a forecasting tool for highway traffic in Morocco.
