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
SSME parameter estimation using radial basis function neural networks
Kevin R. Wheeler,
Atam P. Dhawan
Research output
:
Contribution to conference
›
Paper
›
peer-review
6
Scopus citations
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'SSME parameter estimation using radial basis function neural networks'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Parameter Estimation
100%
Radial Basis Function Neural Network (RBFNN)
100%
Space Shuttle Main Engine
100%
Engine Parameters
100%
High Pressure
33%
Learning Algorithm
33%
Oxidizer
33%
Feedforward Neural Network
33%
Starting Transients
33%
Sensor Failure
33%
Engine Operation
33%
K-means Clustering Algorithm
33%
Quickprop
33%
Discharge Temperature
33%
Sensor Validation
33%
Engineering
Parameter Estimation
100%
Radial Basis Function
100%
Space Shuttle
100%
Main Engine
100%
Transients
33%
Oxidizer
33%
Feedforward
33%
Learning Algorithm
33%
Basis Function
33%
Mean Clustering Algorithm
33%
Input Sensor
33%
Discharge Temperature
33%