Currently Supported Models

Historical Mean

Currently Historical Mean method predicts the flow at a certain time slot according to the historical mean value of a specific number of nearest previous time slots.

ARIMA (Autoregressive Integrated Moving Average)

ARIMA is a simple and widely used time series prediction model.

HMM (Hidden Markov Model)

Hidden Markov Model is a statistical Markov model in which the system being modeled is assumed to be a Markov process with hidden states. It is often used in temporal pattern recognition.

XGBoost

XGBoost is a gradient boosting machine learning algorithm widely used in flow prediction and other machine learning prediction areas.

AMulti-GCLSTM

AMulti-GCLSTM (Attention-Fused Multi-Graph Convolutional LSTM Networks) is our prediction model, which requires extra graph information as input, and combines Graph Convolution LSTM and Attention mechanism.


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