INIS
prediction
100%
optimization
100%
machine learning
100%
randomness
100%
algorithms
100%
forests
100%
design
75%
data
50%
emission
25%
laboratories
25%
mixtures
25%
dynamics
25%
reaction mechanisms
25%
values
25%
environmental impacts
25%
information
25%
construction
25%
raw materials
25%
viscosity
25%
plastics
25%
accuracy
25%
yields
25%
carbon dioxide
25%
portland cement
25%
performance
25%
sodium silicates
25%
compression strength
25%
artificial intelligence
25%
Engineering
Machine Learning Algorithm
100%
Optimization
100%
Activated Concrete
100%
Prediction
100%
Random Forest
100%
Models
42%
Mixing Design
28%
Concrete Mix
28%
Concrete Mixture
14%
Artificial Intelligence
14%
Environmental Impact
14%
Plastic Viscosity
14%
Laboratory
14%
Compressive Strength
14%
Portland Cement Concrete
14%
Mechanisms
14%
Design Code
14%
Fresh Properties
14%
Performance
14%
Design Parameter
14%
Complexity
14%
Sodium Silicate
14%
Yield Stress
14%
Accuracy
14%
Keyphrases
Alkali-activated Cement
100%
Machine Learning Algorithms
100%
Prediction Optimization
100%
Random Forest Machine Learning
100%
Random Forest Regression
42%
Fresh Properties
28%
Concrete Mix Design
28%
CO2 Emissions
14%
Strength Data
14%
Hardened Properties
14%
Slump Value
14%
Dynamic Yield Stress
14%
Artificial Intelligence Techniques
14%
Reaction Mechanism
14%
Plastic Viscosity
14%
Design Case
14%
Concrete Mix
14%
Property Data
14%
Portland Cement Concrete
14%
Environmental Impact
14%
Mechanical Strength
14%
Sodium Silicate
14%
Static-dynamic
14%
Inverse Optimization
14%
Applied Design
14%
Compressive Strength
14%
Mixing Parameters
14%
Alternative Building Material
14%
Design Codes
14%
Material Science
Concrete
100%
Concrete Mixture
60%
Mechanical Strength
20%
Portland Cement
20%
Yield Stress
20%
Viscosity
20%
Raw Material
20%
Silicate
20%
Building Material
20%
Compressive Strength
20%
Plastics
20%
Sodium
20%
Carbon Dioxide
20%