A Neighborhood-Augmented LSTM Model for Taxi-Passenger Demand Prediction
Gespeichert in:
Veröffentlicht in: | MASTER (1. : 2019 : Würzburg) Multiple-aspect analysis of semantic trajectories |
---|---|
1. Verfasser: | |
Weitere Verfasser: | , , |
Format: | UnknownFormat |
Sprache: | eng |
Veröffentlicht: |
2020
|
Schlagworte: | |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Titel | Jahr | Verfasser |
---|---|---|
Online Long-Term Trajectory Prediction Based on Mined Route Patterns | 2020 | Petrou, Petros |
Predicting Fishing Effort and Catch Using Semantic Trajectories and Machine Learning | 2020 | Adivi, Pedram |
Uncovering Hidden Concepts from AIS Data: A Network Abstraction of Maritime Traffic for Anomaly DetectionIoannis | 2020 | Kontopoulos,Ioannis |
EvolvingClusters: Online Discovery of Group Patterns in Enriched Maritime Data | 2020 | Theodoropoulos, George S. |
Learning from Our Movements - The Mobility Data Analytics Era | 2020 | Theodoridis, Yannis |
Prospective Data Model and Distributed Query Processing for Mobile Sensing Data Streams | 2020 | Brahem, Mariem |
Multi-channel Convolutional Neural Networks for Handling Multi-dimensional Semantic Trajectories and Predicting Future Semantic Locations | 2020 | Karatzoglou, Antonios |
Nowcasting Unemployment Rates with Smartphone GPS Data | 2020 | Moriwaki, Daisuke |
A Neighborhood-Augmented LSTM Model for Taxi-Passenger Demand Prediction | 2020 | Quy, Tai Le |