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Unsupervised Knowledge Adaptation for Passenger Demand Forecasting
These multimodal forecasting models can improve accuracy but be less practical when different parts of multimodal datasets are owned by different institutions who cannot directly share data among them.
Knowledge Adaption for Demand Prediction based on Multi-task Memory Neural Network
Accurate demand forecasting of different public transport modes(e. g., buses and light rails) is essential for public service operation. However, the development level of various modes often varies sig-nificantly, which makes it hard to predict the demand of the modeswith insufficient knowledge and sparse station distribution (i. e., station-sparse mode).
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