Skip to main navigation
Skip to search
Skip to main content
Arizona State University Home
Home
Profiles
Departments and Centers
Scholarly Works
Activities
Equipment
Grants
Datasets
Prizes
Search by expertise, name or affiliation
Bayesian entropy network for fusion of different types of information
Yuhao Wang,
Yongming Liu
AIMS Consortium
Adaptive Intelligent Materials and Systems Center (AIMS)
Mechanical and Aerospace Engineering
Materials Science and Engineering
Complex System Safety, Center for
Research output
:
Contribution to journal
›
Article
›
peer-review
34
Scopus citations
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Bayesian entropy network for fusion of different types of information'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Information Type
100%
Bayesian Maximum Entropy
100%
Point Observations
66%
Information Data
33%
Range Data
33%
Engineering Problems
33%
Observational Data
33%
Proposed Methodology
33%
Bayesian Methods
33%
Bayesian Network
33%
Posterior Distribution
33%
Information Fusion
33%
Engineering Application
33%
Hybrid Method
33%
Number of Points
33%
Point Data
33%
Adaptive Algorithm
33%
Statistical Information
33%
Distribution Estimation
33%
Maximum Entropy Method
33%
Information Constraints
33%
Engineering
Observation Point
100%
Engineering Problem
50%
Data Point
50%
Posterior Distribution
50%
Maximum Entropy
50%
Engineering Application
50%
Entropy Method
50%
Hybrid Method
50%
Computer Science
Observation Point
100%
Engineering Problem
50%
Bayesian Networks
50%
Engineering Application
50%
Maximum Entropy
50%
Adaptive Algorithm
50%
Statistical Information
50%
Posterior Distribution
50%