1. Forest Fires: This is a difficult regression task, where the aim is to predict the burned area of forest fires, in the northeast region of Portugal, by using meteorological and other data (see details at: http://www.dsi.uminho.pt/~pcortez/forestfires). 2. Solar Flare: Each class attribute counts the number of solar flares of a certain class that occur in a 24 hour period 3. Bias correction of numerical prediction model temperature forecast: It contains fourteen numerical weather prediction (NWP)'s meteorological forecast data, two in-situ observations, and five geographical auxiliary variables over Seoul, South Korea in the summer.
4. Electrical Grid Stability Simulated Data : The local stability analysis of the 4-node star system (electricity producer is in the center) implementing Decentral Smart Grid Control concept. 5. Superconductivty Data: Two file s contain data on 21263 superconductors and their relevant features. 6. Beijing PM2.5 Data: This hourly data set contains the PM2.5 data of US Embassy in Beijing. Meanwhile, meteorological data from Beijing Capital International Airport are also included. 7. PM2.5 Data of Five Chinese Cities: This hourly data set contains the PM2.5 data in Beijing, Shanghai, Guangzhou, Chengdu and Shenyang. Meanwhile, meteorological data for each city are also included. 8. Beijing Multi-Site Air-Quality Data: This hourly data set considers 6 main air pollutants and 6 relevant meteorological variables at multiple sites in Beijing. | 
