Forecasting daily PM₁₀ concentrations in Seoul using various data mining techniques

Mathematics

• Linear Regression Model 100%
• Data Mining Technique 100%
• Randomforest 66%
• Time Series Model 33%
• Forecasting Model 33%
• Support Vector Machine 33%
• Neural Network 33%
• Linear Regression Analysis 33%
• Auto Regressive Integrated Moving Average 33%

Earth and Planetary Sciences

• Air Pollution 100%
• Particular Matter 2.5 66%
• Time Series 33%
• Support Vector Machine 33%

Agricultural and Biological Sciences

• Air Pollution 100%
• Neural Network 33%
• Support Vector Machine 33%
• Linear Models 33%