Submitted to Introduction to Machine Learning (CS480/680, 2020 Spring).
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Updated
Sep 11, 2020 - Python
Submitted to Introduction to Machine Learning (CS480/680, 2020 Spring).
Pytorch implementation of Spatio-temporal Differential Equation Network (STDEN).
Bilgisayar Mühendisliği Bölümü Bilgisayar (Ara) Projesi
This project is intended to create, develop and tune a neural network to predict traffic flow. The data provided was intended to be a list of log records written every 1 hour about the city of Braga, Portugal containing information about temperature, humidity, rain, traffic flow, etc. The data was incomplete, days were missing, there were hour g…
Predict traffic flow by affinity propagation clustering and LSTM
ST-MAN: Spatio-Temporal Multimodal Attention Network for Traffic Prediction (KSEM 2023)
Traffic flow prediction using Spatio-Temporal Residual Networks
A project leverages external data (traffic incidents, weather) to predict traffic flow. Graph is used to model the complex relationship of data.
🌎 🚙📚 Predicting travel times and traffic density on a highway in Slovenia
A Pytorch Implementation of Pattern Sensitive Network (PSN)
DeepSTD: Mining Spatio-temporal Disturbances of Multiple Context Factors for Citywide Traffic Flow Prediction
2022年讯飞开发者大赛-考虑时空依赖及全局要素的城市道路交通流量预测挑战赛-Top3解决方案
Long Short-Term Memory(LSTM) is a particular type of Recurrent Neural Network(RNN) that can retain important information over time using memory cells. This project includes understanding and implementing LSTM for traffic flow prediction along with the introduction of traffic flow prediction, Literature review, methodology, etc.
Attention Feature Fusion base on spatial-temporal Graph Convolutional Network(AFFGCN)
M-LibCity: An Open Source Library for Urban Spatio-temporal Prediction Models Based on MindSpore
[ICML'2024] "FlashST: A Simple and Universal Prompt-Tuning Framework for Traffic Prediction"
Ambient Sensorization Techniques to monitor the traffic flow in Braga
Official repo for the following paper: Traffic Forecasting on New Roads Unseen in the Training Data Using Spatial Contrastive Pre-Training (SCPT) (ECML PKDD DAMI '23)
This work considers combine multi-tricks with highway network to achieve traffic flow prediction accurately.
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