This is the implementation code for the paper, "A Dynamic Spatial-temporal Attention Network for Early Anticipation of Traffic Accidents"

Multi-dimensional Analytics Project on Road Accidents of India.

An analysis of traffic accident data for the UK in 2014, using data from the UK Data Service. (Sourced from Kaggle with original data coming from UK Data Service. See wiki for complete citations.)

Automatic detection and alert of vehicle accidents

A hybrid AI model for predicting failures in water distribution systems using Adaptive Neuro-Fuzzy Inference System (ANFIS). The model integrates Genetic Algorithms (GA) and Ant Colony Optimization (ACO) to improve the accuracy of accident prediction.

An end-to-end accident severity prediction project that predicts the seriousness of injury based on various features, using a multiclass classification model.

Модель прогнозирования риска ДТП для каршеринга с F1 0.674 на основе нейронной сети. Использованы Python, PyTorch, CatBoost, PostgreSQL, Streamlit.

Source Code for Random Forest Accident Severity Prediction Modelling

A comprehensive analysis and classification of accident-prone zones in Australia using historical road crash data, leveraging machine learning models to predict and categorize high-risk areas.

This project analyzes aviation accident data using machine learning to predict and prevent fatal accidents. By testing models like Linear Regression, Random Forest, and XGBoost, the study found XGBoost to be the most accurate in predicting high-risk scenarios, aiding efforts to improve aviation safety.