{"payload":{"pageCount":1,"repositories":[{"type":"Public","name":"osmnx_adjacency_matrix_for_graph_convolutional_networks","owner":"TrafficGCN","isFork":false,"description":"Creating an Adjacency Matrix Using the Dijkstra Algorithm for Graph Convolutional Networks GCNs","allTopics":["python","data-science","graph","graph-algorithms","matrix","osm","traffic","traffic-analysis","dijkstra","dijkstra-algorithm","graph-convolutional-networks","gcn","adjacency-matrix","optimal-route","open-street-map","osmnx","traffic-congestion","metrla"],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":0,"issueCount":0,"starsCount":16,"forksCount":1,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-03-31T13:47:59.233Z"}},{"type":"Public","name":"logo","owner":"TrafficGCN","isFork":false,"description":"","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":1,"forksCount":0,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-11-26T18:45:03.127Z"}},{"type":"Public","name":"haversine_mapping_for_spatial_integration_in_graph_convolutional_networks","owner":"TrafficGCN","isFork":false,"description":"Calculating the nearest weather sensor for each traffic sensor and then merging the weather sensors' temporal data with the traffic sensors'.","allTopics":["python","weather","data-science","data","neural-network","graph","traffic","traffic-analysis","neural-networks","haversine","temporal","haversine-formula","graph-convolutional-networks","gcn","graph-convolutional-network","traffic-congestion","metr-la","t-gcn","pems-bay"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":1,"starsCount":2,"forksCount":1,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-11-23T20:27:42.646Z"}},{"type":"Public","name":"40_cities_osmnx_adjacency_matrices_for_graph_convolutional_networks","owner":"TrafficGCN","isFork":false,"description":"Dijkstra adjacency distance matrices were calculated for 40 cities from traffic sensor locations provide by UTD19 <a href=\"https://utd19.ethz.ch/\" rel=\"nofollow\">https://utd19.ethz.ch/</a>.","allTopics":["matrix","openstreetmap","traffic","traffic-analysis","networkx","dijkstra","dijkstra-algorithm","traffic-prediction","traffic-simulation","dijkstra-shortest-path","adjacency-matrix","networkx-graph","open-street-map","osmnx","graph-neural-networks","traffic-congestion","graph-networks","graph-network","graph-neural-network"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":5,"forksCount":0,"license":"Other","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-11-18T12:23:28.486Z"}},{"type":"Public","name":"optimal_path_dijkstra_for_data_science","owner":"TrafficGCN","isFork":false,"description":"Plotting the Optimal Route in Python for Data Scientists using the Dijkstra Algorithm","allTopics":["python","map","data-science","mapping","osm","dijkstra","dijkstra-algorithm","dijkstra-shortest-path","optimal-route","open-street-map","osmnx"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":10,"forksCount":1,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-02-26T01:57:31.182Z"}},{"type":"Public","name":"mfd_traffic_congestion_for_data_scientists","owner":"TrafficGCN","isFork":false,"description":"Plotting a Macroscopic Fundamental Diagram for Data Scientists in Python for Traffic Flow in Congested Conditions","allTopics":["data-science","traffic","traffic-analysis","traffic-congestion","macroscopic-fundamental-diagram","python","matplotlib"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":1,"forksCount":0,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-02-06T15:23:33.544Z"}}],"repositoryCount":6,"userInfo":null,"searchable":true,"definitions":[],"typeFilters":[{"id":"all","text":"All"},{"id":"public","text":"Public"},{"id":"source","text":"Sources"},{"id":"fork","text":"Forks"},{"id":"archived","text":"Archived"},{"id":"template","text":"Templates"}],"compactMode":false},"title":"TrafficGCN repositories"}