Bayesian Optimized Enhanced Ensemble Multi-Layer Perceptron for Rear-End Collision Prediction in IoV
The trend of creating and deploying intelligent transportation systems within the context of the Internet of Vehicles (IoV) concept is gaining traction and attracting interest from both academia and industry. Rear-end collisions, which constitute an immense amount of traffic accidents, are an essent...
Saved in:
| Main Authors: | Dilna Vijayan, Mohamed Saad, Ahmed M. Khedr |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10804784/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Head injury mechanisms of the occupant under high-speed train rear-end collision
by: Zhenhao Yu, et al.
Published: (2024-09-01) -
Assessment of Rear-End Collision Risk Based on a Deep Reinforcement Learning Technique: A Break Reaction Assessment Approach
by: Muhammad Sameer Sheikh, et al.
Published: (2025-01-01) -
Advanced techniques for wind energy production forecasting: Leveraging multi-layer Perceptron + Bayesian optimization, ensemble learning, and CNN-LSTM models
by: Seyed Matin Malakouti, et al.
Published: (2024-12-01) -
IoV vertical handoff research based on Bayesian decision
by: Cun-qun FAN, et al.
Published: (2013-07-01) -
Integrating Bayesian Network and Cloud Model to Probabilistic Risk Assessment of Maritime Collision Accidents in China’s Coastal Port Waters
by: Zhuang Li, et al.
Published: (2024-11-01)