Forecasting daily PM₁₀ concentrations in Seoul using various data mining techniques

Mathematics

• Forecast 79%
• Data Mining 77%
• Forecasting 77%
• Air Pollution 57%
• Linear Regression Model 53%
• Random Forest 39%
• ARFIMA 20%
• ARIMA 20%
• Weather 18%
• Boosting 18%
• Support Vector Machine 16%
• Time Series Models 15%
• Model 13%
• Policy 13%
• Neural Networks 12%
• Gradient 10%
• Class 3%

Business & Economics

• Data Mining 100%
• Linear Regression Model 61%
• Air Pollution 46%
• Beijing 30%
• Support Vector Machine 22%
• Power Station 18%
• Neural Networks 16%
• Gradient 14%
• Time Series Models 14%
• Boosting 14%
• Weather 13%
• Korea 11%
• Policymaker 11%
• Coast 10%

Engineering & Materials Science

• Data mining 55%
• Air pollution 38%
• Linear regression 34%
• Coastal zones 12%
• Time series 9%
• Support vector machines 9%
• Neural networks 6%