Skip to main navigation
Skip to search
Skip to main content
Torrens University Australia Home
Search content at Torrens University Australia
Home
Profiles
Research Units
Research Outputs
Research Projects
Research Prizes
Press/Media
Adhesion level identification in wheel-rail contact using deep neural networks
Tayab Din Memon
Design and Creative Technology
Research output
:
Contribution to journal
›
Article
›
peer-review
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Adhesion level identification in wheel-rail contact using deep neural networks'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Deep Neural Network
100%
Wheel-rail Contact
100%
Adhesion
100%
Adhesion Condition
66%
Data-driven Algorithm
66%
Monitoring System
33%
Python
33%
Wear Development
33%
Force Characterization
33%
Rail Wear Prediction
33%
Wheel-rail Wear
33%
Braking Force
33%
Sequential Data
33%
Traction Force
33%
Nonlinear Function
33%
Wheelset
33%
Engineering
Deep Neural Network
100%
Adhesion Condition
66%
Monitoring System
33%
Nonlinear Function
33%
Computer Science
Deep Neural Network
100%
Proper Operation
33%
Nonlinear Function
33%
Monitoring System
33%
Python
33%