Cover Image

Estimating City-wide Operating Mode Distribution of Light-Duty Vehicles: A Neural Network-based Approach

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Usama, Muhammad, Koutsopoulos, Haris N., He, Zhengbing, Wang, Lijiao
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Estimating link level traffic emissions: enhancing MOVES with open-source data
by: Wang, Lijiao, et al.
Published: (2025)

Real Time Headway Predictions in Urban Rail Systems and Implications for Service Control: A Deep Learning Approach
by: Usama, Muhammad, et al.
Published: (2025)

Uncertainty Quantification of Spatiotemporal Travel Demand with Probabilistic Graph Neural Networks
by: Wang, Qingyi, et al.
Published: (2023)

Advancing Transportation Mode Share Analysis with Built Environment: Deep Hybrid Models with Urban Road Network
by: Zhuang, Dingyi, et al.
Published: (2024)

Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis
by: Nippani, Abhinav, et al.
Published: (2023)

Learning Multimodal Embeddings for Traffic Accident Prediction and Causal Estimation
by: Zhang, Ziniu, et al.
Published: (2025)

Joint Estimation and Prediction of City-wide Delivery Demand: A Large Language Model Empowered Graph-based Learning Approach
by: Nie, Tong, et al.
Published: (2024)

Distributional Reinforcement Learning with Information Bottleneck for Uncertainty-Aware DRAM Equalization
by: Usama, Muhammad, et al.
Published: (2026)

Explainability and Continual Learning meet Federated Learning at the Network Edge
by: Tsouparopoulos, Thomas, et al.
Published: (2025)

RAST-MoE-RL: A Regime-Aware Spatio-Temporal MoE Framework for Deep Reinforcement Learning in Ride-Hailing
by: Tang, Yuhan, et al.
Published: (2025)

A Neural Operator based on Dynamic Mode Decomposition
by: Sakovich, Nikita, et al.
Published: (2025)

Deep Reinforcement Learning-Based DRAM Equalizer Parameter Optimization Using Latent Representations
by: Usama, Muhammad, et al.
Published: (2025)

Learning-Driven Exploration for Reinforcement Learning
by: Usama, Muhammad, et al.
Published: (2019)

Representing Neural Network Layers as Linear Operations via Koopman Operator Theory
by: Aswani, Nishant Suresh, et al.
Published: (2024)

CoNOAir: A Neural Operator for Forecasting Carbon Monoxide Evolution in Cities
by: Bedi, Sanchit, et al.
Published: (2025)

Network-wide Freeway Traffic Estimation Using Sparse Sensor Data: A Dirichlet Graph Auto-Encoder Approach
by: Zhou, Qishen, et al.
Published: (2025)

LLM-based Content Classification Approach for GitHub Repositories by the README Files
by: Mehmood, Malik Uzair, et al.
Published: (2025)

NeuralMOVES: A lightweight and microscopic vehicle emission estimation model based on reverse engineering and surrogate learning
by: Ramirez-Sanchez, Edgar, et al.
Published: (2025)

A Hybrid Surrogate for Electric Vehicle Parameter Estimation and Power Consumption via Physics-Informed Neural Operators
by: Lim, Hansol, et al.
Published: (2025)

MM-STFlowNet: A Transportation Hub-Oriented Multi-Mode Passenger Flow Prediction Method via Spatial-Temporal Dynamic Graph Modeling
by: Zhang, Ronghui, et al.
Published: (2025)

Is Monotonic Sampling Necessary in Diffusion Models?
by: Khan, Muhammad Haris
Published: (2026)

Memory-Augmented Architecture for Long-Term Context Handling in Large Language Models
by: Shinwari, Haseeb Ullah Khan, et al.
Published: (2025)

Personalized Federated Learning with Exact Stochastic Gradient Descent
by: Nikoloutsopoulos, Sotirios, et al.
Published: (2022)

Neural Network Approach to Stochastic Dynamics for Smooth Multimodal Density Estimation
by: Zarezadeh, Z., et al.
Published: (2025)

Explainable Neural Networks with Guarantees: A Sparse Estimation Approach
by: Ledent, Antoine, et al.
Published: (2025)

SafeBench-Seq: A Homology-Clustered, CPU-Only Baseline for Protein Hazard Screening with Physicochemical/Composition Features and Cluster-Aware Confidence Intervals
by: Khan, Muhammad Haris
Published: (2025)

Joint Explainability-Performance Optimization With Surrogate Models for AI-Driven Edge Services
by: Charalampakos, Foivos, et al.
Published: (2025)

Graph Neural Networks for Pressure Estimation in Water Distribution Systems
by: Truong, Huy, et al.
Published: (2023)

When Context Is Not Enough: Modeling Unexplained Variability in Car-Following Behavior
by: Zhang, Chengyuan, et al.
Published: (2025)

Approximation by Steklov Neural Network Operators
by: Karaman, S. N., et al.
Published: (2024)

ARD-LoRA: Dynamic Rank Allocation for Parameter-Efficient Fine-Tuning of Foundation Models with Heterogeneous Adaptation Needs
by: Shinwari, Haseeb Ullah Khan, et al.
Published: (2025)

Integrating Meteorological and Operational Data: A Novel Approach to Understanding Railway Delays in Finland
by: Borin, Vinicius Pozzobon, et al.
Published: (2026)

Optimizing Luxury Vehicle Dealership Networks: A Graph Neural Network Approach to Site Selection
by: Carocci, Luca Silvano, et al.
Published: (2024)

When Graph Neural Networks Meet Dynamic Mode Decomposition
by: Shi, Dai, et al.
Published: (2024)

DistributedEstimator: Distributed Training of Quantum Neural Networks via Circuit Cutting
by: Singh, Prabhjot, et al.
Published: (2026)

Damper-B-PINN: Damper Characteristics-Based Bayesian Physics-Informed Neural Network for Vehicle State Estimation
by: Zeng, Tianyi, et al.
Published: (2025)

Neural Port-Hamiltonian Models for Nonlinear Distributed Control: An Unconstrained Parametrization Approach
by: Zakwan, Muhammad, et al.
Published: (2024)

Transformers as Implicit State Estimators: In-Context Learning in Dynamical Systems
by: Akram, Usman, et al.
Published: (2024)

MODNO: Multi Operator Learning With Distributed Neural Operators
by: Zhang, Zecheng
Published: (2024)

Deep Neural Networks are Adaptive to Function Regularity and Data Distribution in Approximation and Estimation
by: Liu, Hao, et al.
Published: (2024)