Research Article
A Destination Prediction Network Based on Spatiotemporal Data for Bike-Sharing
Algorithm 1
Candidate generation algorithm.
Input: Training set | Output: Candidate Set | 1:Initialize the time ranges in training set | 2:Select the data items from training set at time | 3:Get according to users, origins and destinations with FPG at minimum | support | 4:Get according to users and origins with FPG at minimum support | 5:Get according to users and destination positions with FPG at minimum | support | 6:Get according to origins and destination positions with FPG at minimum | support | 7:Get the final candidates | 8:Return the candidate set |
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