Coupled-Perception-Framework-for-Road-Condition-Assessment
收藏NIAID Data Ecosystem2026-05-10 收录
下载链接：
https://data.mendeley.com/datasets/fd5h9s2vbc
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资源简介：
Coupled-Perception-Framework-for-Road-Condition-Assessment
This study introduces an innovative approach for high-precision International Roughness Index (IRI) estimation using low-cost telemetry data, addressing the balance between cost and accuracy in road condition assessment.
Project Structure
data/: Contains the dataset used in this paper.
optuna/: Includes all base model experiments, enhanced model and ablation study experiments, visualization code, SHAP model interpretation code, and all figures in the paper.
Filter.py: The filter designed in this paper.
environment.yml: Environment configuration file.
Environment Configuration
This project was developed on a workstation with the following specifications:
OS: Windows 11
CPU: Intel Core i7-12700K
GPU: NVIDIA GeForce RTX 3080
RAM: 32GB DDR4
Python: 3.13.5
Key Libraries: PyTorch, Optuna, Scikit-learn, Matplotlib, Pandas, NumPy
创建时间：
2026-02-10
