查看文章

Demand for electric kickboards is increasing specifically in tourist‐centric regions worldwide. In order to gain a competitive edge and to provide quality service to customers, it is essential to properly deploy rental electric kickboards (e‐kickboards) at the time and place customers want. However, it is necessary to study how to divide the region to predict electric mobility demand by region. Therefore, this study is made to more accurately predict future demand based on past regional customers’ electric mobility demand data. We have proposed a novel electric kickboard demand prediction in spatiotemporal dimension using clustering‐aided bagging regressor. We have used electric kickboard usage data from a Jeju, South Korea‐based company. As a result of the experiment, it was found that the accuracy before using clustering‐based bagging regressor and when the region was divided by the clustering method, the …