An Adaptive Vehicle Location Prediction Using Machine Learning: A Case Study of Campus Shuttle Bus
Vehicle location prediction and the use of vehicle location tracking are increasingly important topics of discussion among connected vehicle researchers. Location tracking for mobile users is essential due to the correlated services and to improve the quality of service; however, it is challenging....
Saved in:
| Main Authors: | Tarak Nandy, Raenu Kolandaisamy, Rafidah Md Noor, Sananda Bhattacharyya |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10971389/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
COMPARISON OF SARIMA, SVR, AND GA-SVR METHODS FOR FORECASTING THE NUMBER OF RAINY DAYS IN BENGKULU CITY
by: Novi Puspita, et al.
Published: (2022-03-01) -
A new hybrid model SARIMA-ETS-SVR for seasonal influenza incidence prediction in mainland China
by: Daren Zhao, et al.
Published: (2023-11-01) -
Time series study of climate variables utilising a seasonal ARIMA technique for the Indian states of Punjab and Haryana
by: Pankaj Dahiya, et al.
Published: (2024-11-01) -
Forecasting Bronchopneumonia Disease Using the SARIMA Method: A Case Study at Hospital X
by: Mursyidul Ibad
Published: (2025-03-01) -
SentiTSMixer: A Specific Model for Sales Forecasting Using Sentiment Analysis of Customer
by: Partha Ghosh, et al.
Published: (2025-01-01)