Online car-hailing order demand prediction method based on space-time context attention network
A space-time context and demand forecasting technology, applied in biological neural network models, data processing applications, instruments, etc., can solve problems such as the inability to accurately predict the demand for online car-hailing orders
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[0055] An embodiment of the present invention provides a method for forecasting online car-hailing order demand based on a spatio-temporal contextual attention network, which is used to improve the technical problem of being unable to accurately predict online car-hailing order demand.
[0056] Main inventive idea of the present invention is as follows:
[0057] Based on the relevant knowledge in the field of deep learning and transportation planning, considering the spatial relationship between urban ride-hailing areas and the time dependence of historical orders, a demand prediction method for online car-hailing orders based on spatio-temporal contextual attention networks is proposed. This method fully considers the spatial location of the urban region itself, the relationship between different regions, and the time dependence of historical orders in multiple time periods on the demand for online car-hailing orders, so as to improve the accuracy of urban regional online ca...
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