Research
On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

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0111 · Oct 201919922001200920172026
5 results for Louisiana

This study uses ARM to analyze pedestrian crashes under different lighting conditions.

problem Identifying crash risk factors under varying lighting conditions.
method Applied Association Rules Mining to Louisiana pedestrian crash data.
result Daylight crashes are associated with children, seniors, and older drivers.

Study uses vehicle trajectory data to predict traffic incidents on highways.

problem Early detection of traffic incidents to reduce secondary crashes.
method Machine learning algorithms (Logistic Regression, Random Forest, Extreme Gradient Boost, Artificial Neural Network) applied to vehicle trajectory data.
result Random Forest model performs best for incident prediction.

Predict real-time crash risks during hurricane evacuations using connected vehicle data.

problem Mitigate crash risks during hurricane evacuations by predicting high-risk locations.
method Used connected vehicle data to predict crash risks in real-time, considering weather and traffic features.
result Gaussian Process Boosting and Extreme Gradient Boosting models performed best, with recall of 0.91.

This study identifies RwD crash patterns on rural two-lane highways under different lighting conditions.

problem Insufficient investigation of RwD crashes under varying lighting conditions.
method Data mining using association rules mining (ARM) on crash database.
result Interesting crash patterns and risk factors identified under different lighting conditions.