Analyzing feature importance for older pedestrian crash severity: A comparative study of DNN models, emphasizing road and vehicle types with SHAP interpretation
Recognizing the importance of road safety modeling, the study explores Deep Neural Networks (DNN) with features like hidden layers, batch normalization, Rectified Linear Unit (ReLU) activation, and dropout to predict crash severity, interpreting decisions using SHapley Additive exPlanations (SHAP) f...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
|
| Series: | Multimodal Transportation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772586325000176 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|