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Integration of grey model and neural network for robotic application
Shih-Hung Yang
, Jung Che Li
, Yon Ping Chen
Department of Mechanical Engineering
Research output
:
Chapter in Book/Report/Conference proceeding
›
Conference contribution
2
Citations (Scopus)
Overview
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Keyphrases
Network Model
100%
Neural Network
100%
Feedforward Neural Network
100%
Grey Model
100%
Robotic Applications
100%
GM(1,1)
50%
Grey Prediction Model
33%
Intelligent Prediction
33%
First-order
16%
Systems-based
16%
Number of Parameters
16%
Predictive Value
16%
Prediction Error
16%
Target Tracking
16%
Levenberg-Marquardt Algorithm
16%
Trajectory Prediction
16%
Grey GM(1,1) Model
16%
Batch Training
16%
Computer Science
Neural Network
100%
Feedforward Neural Network
100%
gray model
100%
Robotics Application
100%
Prediction Phase
66%
Model Prediction
33%
Tracking (Position)
16%
Experimental Result
16%
Prediction Error
16%
Levenberg Marquardt
16%
Single Variable
16%
Engineering
Feedforward
100%
Robotics Application
100%
Model Prediction
33%
Levenberg-Marquardt Algorithm
16%
Experimental Result
16%
Tracking (Position)
16%
One Step
16%
Prediction Error
16%
Target Tracking
16%
Chemical Engineering
Neural Network
100%
Feedforward Neural Network
100%