Copertina

Horizon-Aware Forecasting of Passenger Assistance Demand for Rail Station Workforce Planning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Sheehan, Michael, Timoshenko, Irina
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Applications Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Context-Aware Automated Passenger Counting Data Denoising
di: Cherrier, Noëlie, et al.
Pubblicazione: (2024)

Predicting the Skies: A Novel Model for Flight-Level Passenger Traffic Forecasting
di: Ehsani, Sina, et al.
Pubblicazione: (2024)

DemandLens: Enhancing Forecast Accuracy Through Product-Specific Hyperparameter Optimization
di: Pillai, Srijesh, et al.
Pubblicazione: (2025)

Demand Forecasting for Platelet Usage: from Univariate Time Series to Multivariate Models
di: Motamedi, Maryam, et al.
Pubblicazione: (2021)

Forecasting Monthly Residential Natural Gas Demand Using Just-In-Time-Learning Modeling
di: Alakent, Burak, et al.
Pubblicazione: (2025)

Forecasting Medium-Horizon Alzheimer's Disease Progression: Residual Gap-Aware Transformers for 24-Month CDR-SB Change from ADNI Clinical and Biomarker Histories
di: Tong, Ran, et al.
Pubblicazione: (2026)

AutoML Algorithms for Online Generalized Additive Model Selection: Application to Electricity Demand Forecasting
di: Das, Keshav, et al.
Pubblicazione: (2025)

Enhanced Renewable Energy Forecasting using Context-Aware Conformal Prediction
di: Moradi, Alireza, et al.
Pubblicazione: (2025)

Diabetes Lifestyle Medicine Treatment Assistance Using Reinforcement Learning
di: Tang, Yuhan
Pubblicazione: (2025)

ForeSWE: Forecasting Snow-Water Equivalent with an Uncertainty-Aware Attention Model
di: Thapa, Krishu K, et al.
Pubblicazione: (2025)

Copula-Based Aggregation and Context-Aware Conformal Prediction for Reliable Renewable Energy Forecasting
di: Moradi, Alireza, et al.
Pubblicazione: (2026)

DRL-STAF: A Deep Reinforcement Learning Framework for State-Aware Forecasting of Complex Multivariate Hidden Markov Processes
di: Jiang, Manrui, et al.
Pubblicazione: (2026)

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

A Novel Hybrid Approach to Contraceptive Demand Forecasting: Integrating Point Predictions with Probabilistic Distributions
di: Hewage, Harsha Chamara, et al.
Pubblicazione: (2025)

Enhancing Uncertain Demand Prediction in Hospitals Using Simple and Advanced Machine Learning
di: Hu, Annie, et al.
Pubblicazione: (2024)

Informed Forecasting: Leveraging Auxiliary Knowledge to Boost LLM Performance on Time Series Forecasting
di: Ghasemloo, Mohammadmahdi, et al.
Pubblicazione: (2025)

Federated Learning for Financial Forecasting
di: Noseda, Manuel, et al.
Pubblicazione: (2025)

Data-driven Calibration Sample Selection and Forecast Combination in Electricity Price Forecasting: An Application of the ARHNN Method
di: Serafin, Tomasz, et al.
Pubblicazione: (2025)

Copyright and Competition: Estimating Supply and Demand with Unstructured Data
di: Han, Sukjin, et al.
Pubblicazione: (2025)

Improving Geopolitical Forecasts with Bayesian Networks
di: Martin, Matthew
Pubblicazione: (2026)

Simplifying Random Forests' Probabilistic Forecasts
di: Koster, Nils, et al.
Pubblicazione: (2024)

DeepMIDE: A Multi-Output Spatio-Temporal Method for Ultra-Scale Offshore Wind Energy Forecasting
di: Ye, Feng, et al.
Pubblicazione: (2024)

Monitoring Machine Learning Forecasts for Platform Data Streams
di: Rombouts, Jeroen, et al.
Pubblicazione: (2024)

Adaptive Multi-task Learning for Probabilistic Load Forecasting
di: Zaballa, Onintze, et al.
Pubblicazione: (2025)

Multidata Causal Discovery for Statistical Hurricane Intensity Forecasting
di: S, Saranya Ganesh, et al.
Pubblicazione: (2025)

Forecasting West Nile virus with deep graph encoders
di: Greiffenstein, Ethan, et al.
Pubblicazione: (2025)

Transportation Marketplace Rate Forecast Using Signature Transform
di: Gu, Haotian, et al.
Pubblicazione: (2024)

Transfer Learning using 66 Diseases for Disease Forecasting Applications
di: Beesley, Lauren J, et al.
Pubblicazione: (2026)

Deep Autocorrelation Modeling for Time-Series Forecasting: Progress and Prospects
di: Wang, Hao, et al.
Pubblicazione: (2026)

Evaluating Weather Forecasts from a Decision Maker's Perspective
di: Raeth, Kornelius, et al.
Pubblicazione: (2025)

Forecasting the future development in quality and value of professional football players
di: van Arem, Koen W., et al.
Pubblicazione: (2025)

Distributional Regression U-Nets for the Postprocessing of Precipitation Ensemble Forecasts
di: Pic, Romain, et al.
Pubblicazione: (2024)

Copula Conformal Prediction for Multi-step Time Series Forecasting
di: Sun, Sophia, et al.
Pubblicazione: (2022)

The Living Forecast: Evolving Day-Ahead Predictions into Intraday Reality
di: Bölat, Kutay, et al.
Pubblicazione: (2025)

CLVAE: A Variational Autoencoder for Long-Term Customer Revenue Forecasting
di: Näf, Jeffrey, et al.
Pubblicazione: (2026)

Graph Convolutional Support Vector Regression for Robust Spatiotemporal Forecasting of Urban Air Pollution
di: Jahan, Nourin, et al.
Pubblicazione: (2026)

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting
di: Ahmad, Owais, et al.
Pubblicazione: (2025)

CESAR: A Convolutional Echo State AutoencodeR for High-Resolution Wind Forecasting
di: Bonas, Matthew, et al.
Pubblicazione: (2024)

MMformer with Adaptive Transferable Attention: Advancing Multivariate Time Series Forecasting for Environmental Applications
di: Xin, Ning, et al.
Pubblicazione: (2025)

Signature Kernel Scoring Rule: A Spatio-Temporal Diagnostic for Probabilistic Weather Forecasting
di: Dodson, Archer, et al.
Pubblicazione: (2025)