most citedSmartphone Transportation Mode Recognition Using a Hierarchical Machine Learning Classifier and Pooled Features From Time and Frequency Domains

63 citations · 108 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CY2020

Network and Station-Level Bike-Sharing System Prediction: A San Francisco Bay Area Case Study

Huthaifa I. Ashqar, Mohammed Elhenawy, Hesham A. Rakha +2

The paper develops models for modeling the availability of bikes in the San Francisco Bay Area Bike Share System applying machine learning at two levels: network and station. Inves…

cs.CY2020

Developing a Novel Crowdsourcing Business Model for Micro-Mobility Ride-Sharing Systems: Methodology and Preliminary Results

Mohammed Elhenawy, MD Mostafizur Rahman Komol, Huthaifa I. Ashqar +4

Micro-mobility ride-sharing is an emerging technology that provides access to the transit system with minimum environmental impacts. Significant research is required to ensure that…

cs.CY202044 cited

Modeling bike availability in a bike-sharing system using machine learning

Huthaifa I. Ashqar, Mohammed Elhenawy, Mohammed H. Almannaa +3

This paper models the availability of bikes at San Francisco Bay Area Bike Share stations using machine learning algorithms. Random Forest (RF) and Least-Squares Boosting (LSBoost)…

cs.LG202063 cited

Smartphone Transportation Mode Recognition Using a Hierarchical Machine Learning Classifier and Pooled Features From Time and Frequency Domains

Huthaifa I. Ashqar, Mohammed H. Almannaa, Mohammed Elhenawy +2

This paper develops a novel two-layer hierarchical classifier that increases the accuracy of traditional transportation mode classification algorithms. This paper also enhances cla…

cs.CY20201 cited

A Comparative Analysis of E-Scooter and E-Bike Usage Patterns: Findings from the City of Austin, TX

Mohammed Hamad Almannaa, Huthaifa I. Ashqar, Mohammed Elhenawy +3

E-scooter-sharing and e-bike-sharing systems are accommodating and easing the increased traffic in dense cities and are expanding considerably. However, these new micro-mobility tr…