bbddqiao's repositories
AccidentsSeverityPredictionML
Web app to Predict of US traffic accidents severity based on weather conditions like visibility, temperature and weather categories like rain, snow, foggy etc as well as based on US location and the day of the week.
Traffic-Prediction-Open-Code-Summary
Summary of open source code for deep learning models in the field of traffic prediction
trajectory_mining
trajectory mining tool function implement by python
car_accident_severity_prediction
Predict the severity of traffic delays from potential car accidents using gradient boosted trees!
DSTGCN
codes of Deep Spatio-Temporal Graph Convolutional Network for Traffic Accident Prediction
grid2demand
A tool for generating zone-to-zone travel demand based on grid zones and gravity model
GSNet
AAAI 2021. GSNet: Learning Spatial-Temporal Correlations from Geographical and Semantic Aspects for Traffic Accident Risk Forecasting
How-to-Build-a-Graph-Based-Deep-Learning-Architecture-in-Traffic-Domain
How to Build a Graph-Based Deep Learning Architecture in Traffic Domain
Integrated_modeling_GMNS
AMS data Hub that connects all transportation modeling tools based on GMNS format
MapConflation
Code for Establishing Multisource Data-Integration Framework for Transportation Data Analytics
NYCDatasetProcessing
Preprocessing TaxiNYC Data
osm2rn
A simple Python code to extract road network (in Shapefile) from OpenStreetMap (OSM)
pydriosm
Download, read/parse and import/export OpenStreetMap data extracts
pytorch-lightning
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
RobustVAE
Robuast Variational Autoencoder
Spatio-Temporal-papers
This project is a collection of recent research in areas such as new infrastructure and urban computing, including white papers, academic papers, AI lab and dataset etc.
SPHDM
# SPHDM A Structure based Phish Homology Detection Model (SPHDM) is proposed to detected the phishing web. Thank you for your interests in our work! The dataset we ultilized for training and testing for is reposited in github. Address: https://github.com/qiaodaben/SPHDM/dataset You can download this notebook as well as the well-organized dataset for training and testing. The toy example for visualization is in SPHDM Respository. If you find this work interesting and helpful to your work, please find the citation of the papers as below. Thank you very much. Any question you can email to fengjian@xust.edu.cn
STGCN_IJCAI-18
Spatio-Temporal Graph Convolutional Networks
tptk
A Trajectory Preprocessing Toolkit in Python
transbigdata
A Python package developed for transportation spatio-temporal big data processing and analysis.