Comparative Insights Into E‐Scooter Usage Prediction Through Machine Learning and Deep Learning Techniques

Shared micromobility services are experiencing rapid growth, particularly in addressing last‐mile transportation needs. The most crucial questions focus on identifying the determinants of user behavior and the factors driving demand for micromobility vehicles. Investigating this topic is thus essent...

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Veröffentlicht in:	Journal of advanced transportation Jg. 2025; H. 1
Hauptverfasser:	Yurdakul, Gokhan, Aydin, Nezir, Seker, Sukran, Yu, Hao
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London John Wiley & Sons, Inc 01.01.2025 Wiley
Schlagworte:	Algorithms Ambulation aids Artificial neural networks Bayesian analysis Comparative analysis Datasets Deep learning Demand Electric vehicles Emissions Energy consumption Environmental impact Forecasting Fossil fuels Greenhouse gases Heuristic methods Learning algorithms Machine learning Mathematical models Methods Motor scooters Neural networks Optimization Performance evaluation Rankings Regression analysis Scooters Traffic accidents & safety Traffic congestion Variables
ISSN:	0197-6729, 2042-3195
Online-Zugang:	Volltext
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