Search Results for author: Mohammed Elhenawy

Found 10 papers, 1 papers with code

Hybrid Pointer Networks for Traveling Salesman Problems Optimization

1 code implementation6 Oct 2021 Ahmed Stohy, Heba-Tullah Abdelhakam, Sayed Ali, Mohammed Elhenawy, Abdallah A Hassan, Mahmoud Masoud, Sebastien Glaser, Andry Rakotonirainy

Our network significantly outperforms the original graph pointer network for small and large-scale problems increasing its performance for TSP50 from 5. 959 to 5. 706 without utilizing 2opt, Pointer networks, Attention model, and a wide range of models, producing results comparable to highly tuned and specialized algorithms.

Combinatorial Optimization Graph Embedding +1

A Review on Drivers Red Light Running Behavior Predictions and Technology Based Countermeasures

no code implementations15 Aug 2020 Md Mostafizur Rahman Komol, Jack Pinnow, Mohammed Elhenawy, Shamsunnahar Yasmin, Mahmoud Masoud, Sebastien Glaser, Andry Rakotonirainy

Red light running at signalised intersections is a growing road safety issue worldwide, leading to the rapid development of advanced intelligent transportation technologies and countermeasures.

Modeling bike counts in a bike-sharing system considering the effect of weather conditions

no code implementations13 Jun 2020 Huthaifa I. Ashqar, Mohammed Elhenawy, Hesham A. Rakha

The paper develops a method that quantifies the effect of weather conditions on the prediction of bike station counts in the San Francisco Bay Area Bike Share System.


Vulnerable Road User Detection Using Smartphone Sensors and Recurrence Quantification Analysis

no code implementations12 Jun 2020 Huthaifa I. Ashqar, Mohammed Elhenawy, Mahmoud Masoud, Andry Rakotonirainy, Hesham A. Rakha

RQA features are added to traditional time domain features to investigate the classification accuracy when using binary, four-class, and five-class Random Forest classifiers.

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

no code implementations7 Jun 2020 Mohammed Hamad Almannaa, Huthaifa I. Ashqar, Mohammed Elhenawy, Mahmoud Masoud, Andry Rakotonirainy, Hesham Rakha

Results also show a similar usage pattern for the average speed of e-bikes and e-scooters throughout the days of the week and a different usage pattern for the average speed of e-bikes and e-scooters over the hours of the day.

Topological Stability: a New Algorithm for Selecting The Nearest Neighbors in Non-Linear Dimensionality Reduction Techniques

no code implementations13 Nov 2019 Mohammed Elhenawy, Mahmoud Masoud, Sebastian Glaser, Andry Rakotonirainy

The proposed algorithm then adds new points to the two nearest neighbours based on the distance and the angle between each new point and the orthogonal to the subspace.

Dimensionality Reduction

Impact of Narrow Lanes on Arterial Road Vehicle Crashes: A Machine Learning Approach

no code implementations7 Nov 2019 Mohammed Elhenawy, Arash Jahangiri, Hesham Rakha

The RF was used to compute the importance of the lane width predictors in our regression model based on two different measures.

BIG-bench Machine Learning

Open-plan Glare Evaluator (OGE): A Demonstration of a New Glare Prediction Approach Using Machine Learning Algorithms

no code implementations12 Oct 2019 Ayman Wagdy, Veronica Garcia-Hansen, Mohammed Elhenawy, Gillian Isoardi, Robin Drogemuller, Fatma Fathy

This research aims to demonstrate the validity of this approach by comparing the accuracy of the new ML model for open-plan offices (OGE) to the accuracy of the existing glare metrics using local dataset.

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