## 2 Materials and Methods
### Thailand Air Quality Index  
The study area of this research is the upper northern part of Thailand due to the air pollution problem during summer every year. This area includes 8 provinces: Chiang Mai, Chiang Rai, Lampang, Lamphun, Mae Hongson, Nan, Phayao, Phrae, and Uttaradit. Only fixed-site data monitoring stations from the Pollution Control Department (PCD), Ministry of Natural Resources and Environment, Thailand, were selected to create a prediction model.  
There are 14 fixed-site data monitoring stations in total; each province except Uttaradit has at least one station. The timing of raw data from these stations differs depending on the availability of recorded data from each location. However, the first date for most of the recordings is 1 January 2010 and the recording end date is 30 April 2018 (for additional details, see Appendix A). Considering the completeness of data, only one station per province was selected from all stations. Therefore, there were eight fixed-site data monitoring stations used in this research as follows:  
* Yupparaj Wittayalai School, Chiang Mai (CHM-Yup);
* Natural Resources and Environment Office, Chiang Rai (CHR-Env);
* Lampang Meteorological Station, Lampang (LPA-Met);
* Provincial Administrative Stadium, Lamphun (LPH-Sta);
* Natural Resources and Environment Office, Mae Hongson (MHS-Env);
* Chaloem Phra Kiat Hospital, Nan (NAN-Hos);
* Knowledge Park, Nan (NAN-Hos);
* Phrae Meteorological Station, Phrae (PHA-Met).  
Data from PCD were divided into two groups. The first group was meteorological, including wind speed (WS), wind direction (WD), relative humidity (RH), pressure (PR), rain (RA), temperature (TEMP), and solar radiation (SR). The other group was air pollution data, including PM\({}_{10}\), PM\({}_{2.5}\), ground-level ozone (O\({}_{3}\)), carbon monoxide (CO), nitrogen monoxide (NO), nitrogen dioxide (NO\({}_{2}\)), and sulfur dioxide (SO\({}_{2}\)). Each station records different parameters (for additional details, see Appendix B). According to the investigation, it was found that 6 out of 8 stations with almost all parameters were collected, except PM\({}_{2.5}\), available in only two stations: CHM-Yup and NAN-Hos. In addition, the rain was excluded as an input feature in all data monitoring stations due to numerous zero values with more than 99% during the focus period of the experiment.  
To report the levels of air pollution for people, an air quality index was used. Air pollution concentrations were divided into groups and represented by the color scheme. The number of groups and the range of concentrations in each group differed according to the law of each country. In Thailand, the PCD under the Thai government announced the Thai air quality index (T-AQI) [33] as a standard for classifying air quality. This index selects six air pollutions, namely, PM\({}_{10}\), PM\({}_{2.5}\), O\({}_{3}\), CO, NO\({}_{2}\), and SO\({}_{2}\). In T-AQI calculations, each air pollution was transformed to the T-AQI level by the corresponding equation, then the final T-AQI level reported to people was identified from the maximum value of T-AQI. Both types of PM often have the highest T-AQI levels compared to the other four air pollutions, so this research selected only two types of PM to create a prediction model. There are five groups of T-AQI; therefore, the meaning and ranges of each group were calculated from concentrations of both types of PM, as shown in Table 1.