Global ETD Search

Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.

Results

Showing 1 to 1 of 1 for “"E-scooter demand prediction"”.

  1. Deep Learning for Short-Term Spatiotemporal Prediction of Shared Dockless E-Scooter Demand: Grid-Based Representation, Temporal Input Design, and Day-Type-Aware Model Benchmarking

    Shared electric scooter (e-scooter) systems exhibit dynamic spatiotemporal demand patterns, making accurate short-term prediction critical for fleet rebalancing and operations. Despite growing interest in shared micromobility demand prediction, literature still lacks a coherent image-based deep …

    calgary Repository record for Deep Learning for Short-Term Spatiotemporal Prediction of Shared Dockless E-Scooter Demand: Grid-Based Representation, Temporal Input Design, and Day-Type-Aware Model Benchmarking (opens in a new tab)