Skip to main navigation
Skip to search
Skip to main content
New Jersey Institute of Technology Home
Help & FAQ
Home
Profiles
Research units
Facilities
Federal Grants
Research output
Press/Media
Search by expertise, name or affiliation
Data Analytics for Fault Localization in Complex Networks
Maggie X. Cheng, Wei Biao Wu
MT School of Management
Research output
:
Contribution to journal
›
Article
›
peer-review
18
Scopus citations
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Data Analytics for Fault Localization in Complex Networks'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Communication Systems
50%
Complex Networks
100%
Concentration Properties
50%
Conditional Probability
50%
Data Analytics
100%
Event-based
50%
Fault Hypothesis
100%
Fault Localization
100%
Fault Probability
100%
Fault Propagation
50%
Large Complex Networks
50%
Learning Algorithm
50%
Localization Technique
50%
Logistic Regression
50%
Machine Learning Algorithms
50%
Machine Learning Approach
50%
Multiple Faults
50%
Network Events
100%
New Fault
50%
Prior Probability
50%
Regression Model
50%
Satisfactory Performance
50%
Single Fault
50%
Computer Science
Complex Networks
100%
Conditional Probability
50%
Data Analytics
100%
Experimental Result
50%
Fault Localization
100%
Learning Algorithm
50%
localization algorithm
50%
Logistic Regression
50%
Machine Learning Algorithm
50%
Machine Learning Approach
50%
Prior Probability
50%
Engineering
Communication System
50%
Complex Networks
100%
Conditional Probability
50%
Experimental Result
50%
Learning Algorithm
50%
Learning Approach
50%
Machine Learning Algorithm
50%
Prior Probability
50%