Predictions of PM2.5 concentrations and critical events in Santiago, Chile using Recurrent Neural Networks

Mathematics

• Air Pollution 24%
• Air Quality 28%
• Coefficient of Determination 24%
• Exceed 31%
• Experiment 13%
• Experimental Results 17%
• Health 18%
• Human 15%
• Independent Set 17%
• Lung Cancer 23%
• Model 17%
• Monitoring 17%
• Neural Networks 16%
• Performance 10%
• Pollutants 23%
• Pollution 21%
• Predict 16%
• Prediction 55%
• Preprocessing 20%
• Recurrent Neural Networks 89%
• Spatial Prediction 28%
• Statistical method 16%
• Testing 24%
• Trigger 23%

Business & Economics

• Air 14%
• Air Pollutants 24%
• Air Pollution 19%
• Air Quality 21%
• Chile 69%
• Coefficients 12%
• Experiment 10%
• Human Health 21%
• Lung Cancer 27%
• Monitoring 12%
• Neural Networks 20%
• Performance 6%
• Pollution 15%
• Prediction 56%
• Recurrent Neural Networks 100%
• Statistical Methods 17%
• Testing 29%
• Trigger 15%

Engineering & Materials Science

• Air 19%
• Air pollution 19%
• Air quality 18%
• Experiments 6%
• Health 12%
• Monitoring 9%
• Neural networks 10%
• Pollution 16%
• Recurrent neural networks 72%
• Set theory 11%
• Statistical methods 14%
• Testing 17%