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Modeling of Air Pollutants So2 Elements Using Geographically Weighted Regression (gwr), Geographically Temporal Weighted Regression (gtwr) and Mixed Geographically Temporalweighted Regression (mgtwr)
| Content Provider | Semantic Scholar |
|---|---|
| Author | Winarso, Kukuh Yasin, Hasbi |
| Copyright Year | 2016 |
| Abstract | Sulphur dioxide gas (SO2) is derived from the combustion of fuels containing sulphur. Aside from fuel, sulphur is also contained in the lubricant. Sulphur dioxide gas is difficult to detect because it is colourless gas. Sulphur dioxide can cause respiratory disorders, indigestion, headache, chest pain, and nerve. A necessary preventive measures to reduce the impact of air pollutants SO2 particular elements, one of them by making the modeling that can bring the causes and factors resistor element of air pollutants SO2. The modeling is Geographically Weighted Regression (GWR), Temporal Geographically Weighted Regression (GTWR) and Mixed Geographically Weighted Temporal Regression (MGTWR). All three models are regression models spatial, temporal and spatial temporal spatialcombined, which models the effects of air pollutants SO2 element with a direct view of geography and time of occurrence of air pollution. The third model is then compared to obtain the best model in the modeling of air pollutants SO2 elements. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.arpnjournals.org/jeas/research_papers/rp_2016/jeas_0716_4566.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
