Machine Learning with Variable Sampling Rate for Traffic Prediction in 6G MEC IoT
The high-speed development of mobile broadband networks and IoT applications has brought about massive data transmission and data processing, and severe traffic congestion has adversely affected the fast-growing networks and industries. To better allocate network resources and ensure the smooth oper...
Saved in:
Main Authors: | Rongqun Peng, Xiuhua Fu, Tian Ding |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2022-01-01
|
Series: | Discrete Dynamics in Nature and Society |
Online Access: | http://dx.doi.org/10.1155/2022/8190688 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
IoT in Urban Traffic Prediction Development Case Studies and Future Trends
by: Wang Renhe
Published: (2025-01-01) -
A Comparative Study of Anomaly Detection Techniques for IoT Security Using Adaptive Machine Learning for IoT Threats
by: Dheyaaldin Alsalman
Published: (2024-01-01) -
An Improved Deep Belief Network IDS on IoT-Based Network for Traffic Systems
by: Rayeesa Malik, et al.
Published: (2022-01-01) -
Ontologies for the Transactions on IoT
by: Chao Qu, et al.
Published: (2015-03-01) -
Retracted: An Improved Deep Belief Network IDS on IoT-Based Network for Traffic Systems
by: Journal of Advanced Transportation
Published: (2023-01-01)