Keyphrases
Multi-walled Carbon Nanotubes (MWCNTs)
100%
Nanocomposite Film
100%
Polystyrene
100%
Feedforward Neural Network
100%
Bayesian Regularization
100%
Film Coating
100%
Conductivity Prediction
100%
Carbon Nanotube Nanocomposites
100%
Electrical Conductivity
66%
Conductivity Values
33%
Polystyrene Latex Particles
33%
Mean Absolute Error
16%
Neural Network
16%
Mean Squared Error
16%
Correlation Coefficient
16%
Conductivity Measurement
16%
Sensitivity Analysis
16%
Particle Size
16%
Root Mean Square Error
16%
Network Model
16%
Regression Analysis
16%
Performance Assessment
16%
Back Propagation Algorithm
16%
Performance Results
16%
Surfactant Concentration
16%
Hidden Layer
16%
Weight Value
16%
Carbon Nanotube Film
16%
Bias Value
16%
Assessment Parameters
16%
Training Performance
16%
Optimal Geometry
16%
Network Training
16%
Coating Performance
16%
Bayesian Regulation
16%
Single Output
16%
Coefficient Determination
16%
Engineering
Network Model
100%
Multi-Walled Carbon Nanotube
100%
Nanocomposite
100%
Feedforward
100%
Mean Absolute Error
16%
Good Agreement
16%
Mean-Squared-Error
16%
Size of Particle
16%
Conductivity Measurement
16%
Relative Importance
16%
Backpropagation Algorithm
16%
Single Output
16%
Root-Mean-Squared Error
16%
Hidden Layer
16%
Surfactant
16%
Optimal Geometry
16%
Network Training
16%
Molecular Weight
16%
Molecular Mass
16%
Chemical Engineering
Carbon Nanotube
100%
Polystyrene
100%
Feedforward Neural Network
100%
Film
100%
Surfactant
16%
Neural Network
16%
Material Science
Carbon Nanotube
100%
Polystyrene
100%
Nanocomposite Film
100%
Surface Active Agent
16%
Film
16%
Nanocomposite
16%