INIS
machine learning
100%
transport theory
100%
corrections
100%
prediction
71%
accuracy
42%
errors
42%
emission
28%
dynamics
28%
air quality
28%
atmospherics
28%
roots
14%
imperfections
14%
metrics
14%
hybrids
14%
forecasting
14%
hybrid systems
14%
removal
14%
transport
14%
life cycle
14%
boundary conditions
14%
china
14%
wind
14%
tools
14%
length
14%
inventories
14%
Engineering
Models
100%
Prediction
50%
Accuracy
50%
Particular Matter 2.5
33%
Air Quality
33%
Hybrid
33%
Model Prediction
33%
Field Boundary Condition
16%
Input Source
16%
Longer Term
16%
Error
16%
Metrics
16%
Mean Absolute Error
16%
Dynamic Models
16%
Root Mean Square Error
16%
Lifecycle
16%
Machine Learning Method
16%
Inventory
16%
Chemical Engineering
Learning System
100%
Particular Matter 2.5
50%
Keyphrases
PM2.5 Prediction
28%
Fine Particular Matter
14%