arXiv Open Access 2022

Predicting Citi Bike Demand Evolution Using Dynamic Graphs

Alexander Saff Mayur Bhandary Siddharth Srivastava

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Abstrak

Bike sharing systems often suffer from poor capacity management as a result of variable demand. These bike sharing systems would benefit from models to predict demand in order to moderate the number of bikes stored at each station. In this paper, we attempt to apply a graph neural network model to predict bike demand in the New York City, Citi Bike dataset.

Topik & Kata Kunci

cs.LG

Penulis (3)

Alexander Saff

Mayur Bhandary

Siddharth Srivastava

Format Sitasi

APA MLA BibTeX

Saff, A., Bhandary, M., Srivastava, S. (2022). Predicting Citi Bike Demand Evolution Using Dynamic Graphs. https://arxiv.org/abs/2212.09175

Akses Cepat

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Informasi Jurnal

Tahun Terbit: 2022
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓