Modeling of Ozone Interactions with Various Air Pollutants and Meteorological Factors Using Jaya and Teaching-Learning Based Optimization (TLBO) Algorithms
Ozone (O3), nitrogen oxides (NOx) and carbon monoxide (CO) concentrations and some meteorological parameters measured hourly have been analyzed to examine the interaction patters between O3 and NOx, CO, air temperature, wind speed, relative humidity, and air pressure by taking into account the diurn...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
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Düzce University
2020-07-01
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| Series: | Düzce Üniversitesi Bilim ve Teknoloji Dergisi |
| Subjects: | |
| Online Access: | https://dergipark.org.tr/tr/download/article-file/950981 |
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| Summary: | Ozone (O3), nitrogen oxides (NOx) and carbon monoxide (CO) concentrations and some meteorological parameters measured hourly have been analyzed to examine the interaction patters between O3 and NOx, CO, air temperature, wind speed, relative humidity, and air pressure by taking into account the diurnal variations of them at urban site (Akçaabat ) in Trabzon. Variations of O3 levels have been modeled via Jaya and Teaching-Learning Based Optimization (TLBO) algorithms considering the effects of certain parameters (NOx and CO concentration, air temperature, wind speed, relative humidity, and air pressure) called as the independent variables. The accuracy of Jaya and TLBO methods has been determined and these methods have been carried out with four different functions: quadratic, exponential, linear and power. Some statistical indices have been applied to evaluate the performance of these models. In conclusion, it is shown that Jaya and TLBO algorithms can be used in the optimization of the regression function coefficients in modelling some air pollutants interactions and the best-fit equation for each parameter is obtained from the quadratic function. |
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| ISSN: | 2148-2446 |