Meta-learning over time for destination prediction tasks
A need to understand and predict vehicles' behavior underlies both public and private goals
in the transportation domain, including urban planning and management, ride-sharing …
in the transportation domain, including urban planning and management, ride-sharing …
Forecasting taxi demands using generative adversarial networks with multi-source data
HAH Naji, Q Xue, H Zhu, T Li - Applied Sciences, 2021 - mdpi.com
As a popular transportation mode in urban regions, taxis play an essential role in providing
comfortable and convenient services for travelers. For the sake of tackling the imbalance …
comfortable and convenient services for travelers. For the sake of tackling the imbalance …
Taxi demand prediction using an LSTM-based deep sequence model and points of interest
Nowadays, urban mobility plays an important role in modern cities for city planning,
navigation, and other mobility services. Taxicabs are vital public services in large cities that …
navigation, and other mobility services. Taxicabs are vital public services in large cities that …
[HTML][HTML] Supply level planning for shared e-scooters considering spatiotemporal heteroscedastic demand
Accurate demand forecasting is a key success for mobility service businesses, especially
shared electric (e-) scooters, for their volatile demand, high operational costs, and strict …
shared electric (e-) scooters, for their volatile demand, high operational costs, and strict …
Taxi‐demand forecasting using dynamic spatiotemporal analysis
A Gangrade, P Pratyush, G Hajela - ETRI Journal, 2022 - Wiley Online Library
Taxi‐demand forecasting and hotspot prediction can be critical in reducing response times
and designing a cost effective online taxi‐booking model. Taxi demand in a region can be …
and designing a cost effective online taxi‐booking model. Taxi demand in a region can be …
Learning citywide patterns of life from trajectory monitoring
The recent proliferation of real-world human mobility datasets has catalyzed geospatial and
transportation research in trajectory prediction, demand forecasting, travel time estimation …
transportation research in trajectory prediction, demand forecasting, travel time estimation …
An Ensemble Machine Learning Model To Predictive Analysis of End to End Uber Data
S Tanniru, H Tummala, K Kodali… - 2024 Asia Pacific …, 2024 - ieeexplore.ieee.org
Accurately predicting both daily and monthly transactions is crucial for businesses, providing
invaluable insights to analyze fluctuations and formulate strategic plans effectively. This …
invaluable insights to analyze fluctuations and formulate strategic plans effectively. This …
[PDF][PDF] Transportation Research Interdisciplinary Perspectives
N Saum, M Piantanakulchai, S Sugiura - researchgate.net
Accurate demand forecasting is a key success for mobility service businesses, especially
shared electric (e-) scooters, for their volatile demand, high operational costs, and strict …
shared electric (e-) scooters, for their volatile demand, high operational costs, and strict …