Revealing Toluene Behaviour in the Atmosphere Based on Coupling of Metaheuristics, Xgboost, and Shap

Izdanje: Sinteza 2023 - International Scientific Conference on Information Technology and Data Related Research

DOI: 10.15308/Sinteza-2023-17-22

Oblast: Computer Science and Artificial Intelligence

Stranice: 17-22

Link: https://portal.sinteza.singidunum.ac.rs/paper/902

Apstrakt:
This study used an improved version of the reptilian search algorithm to investigate atmospheric patterns of toluene and its interactions with other polluting species under different environmental conditions. Toluene is a harmful aromatic hydrocarbon known for its role in the formation of secondary atmospheric pollutants. In this study, a two-year database of hourly pollutant concentrations, such as toluene, was analysed. The results were validated against other models using metaheuristic algorithms, and Shapley's additive explanations method was used to interpret them. The findings indicated a distinct correlation between toluene and m,p-xylene, and the study described the environmental conditions that influence their interactions. Overall, this research highlights the significance of using advanced analytical techniques to better understand the relationships between pollutants and their behaviour in different environmental conditions.
Ključne reči: Machine Learning, Extreme Gradient Boosting, Metaheuristics, Explainable Artificial Intelligence, Volatile Organic Compounds
Priložene datoteke:

Preuzimanje citata:

BibTeX format
@article{article,
  author  = {G. Jovanović, M. Perišić, S. Stanišić, N. Bačanin Džakula and A. Stojić}, 
  title   = {Revealing Toluene Behaviour in the Atmosphere Based on Coupling of Metaheuristics, Xgboost, and Shap},
  journal = {Sinteza 2023 - International Scientific Conference on Information Technology and Data Related Research},
  year    = 2023,
  pages   = {17-22},
  doi     = {10.15308/Sinteza-2023-17-22}
}
RefWorks Tagged format
RT Conference Proceedings
A1 Gordana Jovanović
A1 Mirjana Perišić
A1 Svetlana Stanišić
A1 Nebojša Bačanin Džakula
A1 Andreja Stojić
T1 Revealing Toluene Behaviour in the Atmosphere Based on Coupling of Metaheuristics, Xgboost, and Shap
AD Univerzitet Singidunum, Beograd, Beograd, Srbija
YR 2023
NO doi: 10.15308/Sinteza-2023-17-22
Unapred formatirani prikaz citata
G. Jovanović, M. Perišić, S. Stanišić, N. Bačanin Džakula and A. Stojić, Revealing Toluene Behaviour in the Atmosphere Based on Coupling of Metaheuristics, Xgboost, and Shap, Univerzitet Singidunum, Beograd, 2023, doi:10.15308/Sinteza-2023-17-22