Geo-Statistics and Deep Learning-Based Algorithm Design for Real-Time Bus Geo-Location and Arrival Time Estimation Features with Load Resiliency Capacity
This paper introduces a groundbreaking decentralized approach for real-time bus monitoring and geo-location, leveraging advanced geo-statistical and multivariate statistical methods. The proposed long short-term memory (LSTM) model predicts bus arrival times with confidence intervals and reconstruct...
Saved in:
| Main Author: | Smail Tigani |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
|
| Series: | AI |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-2688/6/7/142 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Competitiveness of city geo-brand assessment: selecting the research methodology
by: I. Yu. Aleksandrova
Published: (2023-07-01) -
Cross-View Geo-Localization: A Survey
by: Abhilash Durgam, et al.
Published: (2024-01-01) -
The concept of geo-demographic situation and geo-demographic typology of the subjects of the Russian Federation
by: Fedorov Gennady
Published: (2014-09-01) -
A roll attitude determination method based on the jamming energy of GEO satellites and an LSTM neural network
by: Rundong Li, et al.
Published: (2025-05-01) -
A Wind Turbines Dataset for South Africa: OpenStreetMap Data, Deep Learning Based Geo-Coordinate Correction and Capacity Analysis
by: Maximilian Kleebauer, et al.
Published: (2025-06-01)