Engineering & Materials Science
Decarbonization
100%
Cements
58%
Compressive strength
52%
Machine learning
51%
Concretes
47%
Carbon
37%
Pulverized fuel
14%
Silica fume
12%
Support vector regression
11%
Random forests
10%
Ashes
10%
Construction industry
10%
Slags
9%
Decision trees
9%
Deep neural networks
9%
Mean square error
9%
Sensitivity analysis
8%
Learning algorithms
8%
Energy utilization
7%
Costs
3%
Experiments
3%
Earth & Environmental Sciences
machine learning
70%
compressive strength
56%
cement (construction material)
54%
replacement
40%
carbon
28%
prediction
19%
pulverized fuel ash
15%
perlite
14%
construction industry
11%
fume
11%
blast furnace
10%
slag
9%
energy consumption
8%
sensitivity analysis
8%
material
8%
silica
7%
decision
6%
cost
5%
energy
4%
experiment
3%
parameter
3%
effect
2%
Social Sciences
regression
44%
learning
23%
grid search
23%
energy consumption
14%
neural network
13%
construction industry
13%
assistance
8%
energy
8%
experiment
6%
costs
6%
performance
5%
literature
4%
time
4%