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Machine Learning for Predicting Traffic and Determining Road Capacit
Alex Lewis
, Rina Azoulay
, Esther David
Jerusalem College of Technology
Achva Academic College
Research output
:
Contribution to journal
›
Conference article
›
peer-review
2
Scopus citations
Overview
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Dive into the research topics of 'Machine Learning for Predicting Traffic and Determining Road Capacit'. Together they form a unique fingerprint.
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Keyphrases
Machine Learning
100%
Ensemble Methods
100%
Traffic Flow
100%
Traffic Speed
100%
Road Capacity
100%
K-nearest
100%
Machine Learning Techniques
50%
Feature Selection
50%
Decision Tree
50%
Flow Speed
50%
Linear Regression
50%
Freeway
50%
Auction System
50%
Neural Ensemble
50%
Road Usage
50%
Road Speed
50%
Traffic Dataset
50%
PeMS
50%
Learning Methods
50%
Neural Network Method
50%
Computer Science
Machine Learning
100%
Ensemble Method
100%
Neural Network
50%
Machine Learning Technique
50%
Decision Trees
50%
Related Feature
50%
Primary Objective
50%
Engineering
Road
100%
Nearest Neighbor
33%
Extensive Research
16%
Highway Systems
16%
Flow Speed
16%
Machine Learning Technique
16%
Agricultural and Biological Sciences
Neural Network
100%