Skip to main navigation
Skip to search
Skip to main content
University of Johannesburg Home
Search content at University of Johannesburg
Home
Scholars
Research entities
Research output
Press/Media
Equipment & facilities
Damage identification using committee of neural networks
Tshilidzi Marwala
University of Cambridge
Research output
:
Contribution to journal
›
Article
›
peer-review
81
Citations (Scopus)
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Damage identification using committee of neural networks'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Cylindrical Shell
100%
Modal Properties
100%
Frequency Response Function
100%
Damage Identification
100%
Wavelet Transform
100%
Neural Networks Committee
100%
Mean Square Error
50%
Natural Frequency
50%
Mode Shape
50%
Fault Type
50%
Damage Cases
50%
Mass-spring System
50%
Shape Transform
50%
Experimental Demonstration
50%
Neural Network Method
50%
Natural Modes
50%
Three-degree-of-freedom
50%
Average Mean Square Error
50%
Engineering
Measured Data
100%
Frequency Response Function
100%
Simulated Data
100%
Mean Square Error
100%
Cylindrical Shell
100%
Degree of Freedom
50%
Experimental Result
50%
Mode Shape
50%
Natural Mode
50%
Damper System
50%
Resonant Frequency
50%
Physics
Wavelet Analysis
100%
Neural Network
100%
Resonant Frequency
50%
Degree of Freedom
50%